forked from AFPy/python-docs-fr
1465 lines
60 KiB
Plaintext
1465 lines
60 KiB
Plaintext
# Copyright (C) 2001-2018, Python Software Foundation
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# For licence information, see README file.
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#
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msgid ""
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msgstr ""
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"Project-Id-Version: Python 3\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2023-01-15 22:33+0100\n"
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"PO-Revision-Date: 2022-10-18 12:34+0200\n"
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"Last-Translator: Nicolas Audebert <nicolas+python@audebert.at>\n"
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"Language-Team: FRENCH <traductions@lists.afpy.org>\n"
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"Language: fr\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=UTF-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"X-Generator: Poedit 2.3\n"
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#: library/statistics.rst:2
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msgid ":mod:`statistics` --- Mathematical statistics functions"
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msgstr ":mod:`statistics` — Fonctions mathématiques pour les statistiques"
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#: library/statistics.rst:12
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msgid "**Source code:** :source:`Lib/statistics.py`"
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msgstr "**Code source :** :source:`Lib/statistics.py`"
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#: library/statistics.rst:21
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msgid ""
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"This module provides functions for calculating mathematical statistics of "
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"numeric (:class:`~numbers.Real`-valued) data."
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msgstr ""
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"Ce module fournit des fonctions pour le calcul de valeurs statistiques sur "
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"des données numériques (valeurs réelles de la classe :class:`~numbers.Real`)."
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#: library/statistics.rst:24
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msgid ""
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"The module is not intended to be a competitor to third-party libraries such "
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"as `NumPy <https://numpy.org>`_, `SciPy <https://www.scipy.org/>`_, or "
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"proprietary full-featured statistics packages aimed at professional "
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"statisticians such as Minitab, SAS and Matlab. It is aimed at the level of "
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"graphing and scientific calculators."
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msgstr ""
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"Ce module n'est pas pensé comme substitut à des bibliothèques tierces telles "
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"que `NumPy <https://numpy.org>`_, `SciPy <https://www.scipy.org/>`_ ou des "
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"suites logicielles propriétaires complètes à destination des statisticiens "
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"professionnels comme Minitab, SAS ou Matlab. Ce module se situe au niveau "
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"des calculatrices scientifiques graphiques."
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#: library/statistics.rst:30
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msgid ""
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"Unless explicitly noted, these functions support :class:`int`, :class:"
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"`float`, :class:`~decimal.Decimal` and :class:`~fractions.Fraction`. "
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"Behaviour with other types (whether in the numeric tower or not) is "
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"currently unsupported. Collections with a mix of types are also undefined "
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"and implementation-dependent. If your input data consists of mixed types, "
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"you may be able to use :func:`map` to ensure a consistent result, for "
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"example: ``map(float, input_data)``."
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msgstr ""
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"À moins que cela ne soit précisé différemment, ces fonctions gèrent les "
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"objets :class:`int`, :class:`float`, :class:`~decimal.Decimal` et :class:"
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"`~fractions.Fraction`. Leur bon comportement avec d'autres types (numériques "
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"ou non) n'est pas garanti. Le comportement de ces fonctions sur des "
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"collections mixtes de différents types est indéfini et dépend de "
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"l'implémentation. Si vos données comportement un mélange de plusieurs types, "
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"vous pouvez utiliser :func:`map` pour vous assurer que le résultat est "
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"cohérent, par exemple : ``map(float, input_data)``."
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#: library/statistics.rst:38
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msgid ""
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"Some datasets use ``NaN`` (not a number) values to represent missing data. "
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"Since NaNs have unusual comparison semantics, they cause surprising or "
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"undefined behaviors in the statistics functions that sort data or that count "
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"occurrences. The functions affected are ``median()``, ``median_low()``, "
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"``median_high()``, ``median_grouped()``, ``mode()``, ``multimode()``, and "
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"``quantiles()``. The ``NaN`` values should be stripped before calling these "
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"functions::"
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msgstr ""
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#: library/statistics.rst:68
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msgid "Averages and measures of central location"
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msgstr "Moyennes et mesures de la tendance centrale"
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#: library/statistics.rst:70
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msgid ""
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"These functions calculate an average or typical value from a population or "
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"sample."
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msgstr ""
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"Ces fonctions calculent une moyenne ou une valeur typique à partir d'une "
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"population ou d'un échantillon."
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#: library/statistics.rst:74
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msgid ":func:`mean`"
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msgstr ":func:`mean`"
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#: library/statistics.rst:74
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msgid "Arithmetic mean (\"average\") of data."
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msgstr "Moyenne arithmétique des données."
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#: library/statistics.rst:75
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msgid ":func:`fmean`"
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msgstr ":func:`fmean`"
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#: library/statistics.rst:75
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#, fuzzy
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msgid "Fast, floating point arithmetic mean, with optional weighting."
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msgstr "Moyenne arithmétique rapide en calcul à virgule flottante."
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#: library/statistics.rst:76
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msgid ":func:`geometric_mean`"
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msgstr ":func:`geometric_mean`"
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#: library/statistics.rst:76
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msgid "Geometric mean of data."
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msgstr "Moyenne géométrique des données."
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#: library/statistics.rst:77
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msgid ":func:`harmonic_mean`"
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msgstr ":func:`harmonic_mean`"
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#: library/statistics.rst:77
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msgid "Harmonic mean of data."
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msgstr "Moyenne harmonique des données."
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#: library/statistics.rst:78
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msgid ":func:`median`"
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msgstr ":func:`median`"
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#: library/statistics.rst:78
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msgid "Median (middle value) of data."
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msgstr "Médiane (valeur centrale) des données."
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#: library/statistics.rst:79
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msgid ":func:`median_low`"
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msgstr ":func:`median_low`"
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#: library/statistics.rst:79
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msgid "Low median of data."
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msgstr "Médiane basse des données."
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#: library/statistics.rst:80
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msgid ":func:`median_high`"
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msgstr ":func:`median_high`"
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#: library/statistics.rst:80
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msgid "High median of data."
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msgstr "Médiane haute des données."
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#: library/statistics.rst:81
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msgid ":func:`median_grouped`"
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msgstr ":func:`median_grouped`"
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#: library/statistics.rst:81
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msgid "Median, or 50th percentile, of grouped data."
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msgstr ""
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"Médiane de données groupées, calculée comme le 50\\ :sup:`e` percentile."
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#: library/statistics.rst:82
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msgid ":func:`mode`"
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msgstr ":func:`mode`"
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#: library/statistics.rst:82
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msgid "Single mode (most common value) of discrete or nominal data."
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msgstr ""
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"Mode principal (la valeur la plus représentée) de données discrètes ou "
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"nominales."
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#: library/statistics.rst:83
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msgid ":func:`multimode`"
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msgstr ":func:`multimode`"
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#: library/statistics.rst:83
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#, fuzzy
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msgid "List of modes (most common values) of discrete or nominal data."
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msgstr ""
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"Liste des modes (les valeurs les plus représentées) de données discrètes ou "
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"nominales."
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#: library/statistics.rst:84
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msgid ":func:`quantiles`"
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msgstr ":func:`quantiles`"
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#: library/statistics.rst:84
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msgid "Divide data into intervals with equal probability."
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msgstr "Divise les données en intervalles de même probabilité."
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#: library/statistics.rst:88
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msgid "Measures of spread"
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msgstr "Mesures de la dispersion"
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#: library/statistics.rst:90
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msgid ""
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"These functions calculate a measure of how much the population or sample "
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"tends to deviate from the typical or average values."
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msgstr ""
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"Ces fonctions mesurent la tendance de la population ou d'un échantillon à "
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"dévier des valeurs typiques ou des valeurs moyennes."
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#: library/statistics.rst:94
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msgid ":func:`pstdev`"
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msgstr ":func:`pstdev`"
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#: library/statistics.rst:94
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msgid "Population standard deviation of data."
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msgstr "Écart-type de la population."
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#: library/statistics.rst:95
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msgid ":func:`pvariance`"
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msgstr ":func:`pvariance`"
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#: library/statistics.rst:95
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msgid "Population variance of data."
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msgstr "Variance de la population."
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#: library/statistics.rst:96
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msgid ":func:`stdev`"
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msgstr ":func:`stdev`"
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#: library/statistics.rst:96
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msgid "Sample standard deviation of data."
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msgstr "Écart-type d'un échantillon."
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#: library/statistics.rst:97
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msgid ":func:`variance`"
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msgstr ":func:`variance`"
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#: library/statistics.rst:97
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msgid "Sample variance of data."
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msgstr "Variance d'un échantillon."
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#: library/statistics.rst:101
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msgid "Statistics for relations between two inputs"
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msgstr ""
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#: library/statistics.rst:103
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msgid ""
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"These functions calculate statistics regarding relations between two inputs."
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msgstr ""
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#: library/statistics.rst:106
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#, fuzzy
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msgid ":func:`covariance`"
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msgstr ":func:`variance`"
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#: library/statistics.rst:106
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#, fuzzy
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msgid "Sample covariance for two variables."
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msgstr "Variance d'un échantillon."
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#: library/statistics.rst:107
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#, fuzzy
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msgid ":func:`correlation`"
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msgstr ":func:`mean`"
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#: library/statistics.rst:107
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msgid "Pearson's correlation coefficient for two variables."
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msgstr ""
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#: library/statistics.rst:108
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msgid ":func:`linear_regression`"
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msgstr ":func:`linear_regression`"
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#: library/statistics.rst:108
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msgid "Slope and intercept for simple linear regression."
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msgstr ""
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#: library/statistics.rst:113
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msgid "Function details"
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msgstr "Détails des fonctions"
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#: library/statistics.rst:115
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msgid ""
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"Note: The functions do not require the data given to them to be sorted. "
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"However, for reading convenience, most of the examples show sorted sequences."
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msgstr ""
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"Note : les fonctions ne requièrent pas que les données soient ordonnées. "
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"Toutefois, pour en faciliter la lecture, les exemples utiliseront des "
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"séquences croissantes."
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#: library/statistics.rst:120
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msgid ""
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"Return the sample arithmetic mean of *data* which can be a sequence or "
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"iterable."
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msgstr ""
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"Renvoie la moyenne arithmétique de l'échantillon *data* qui peut être une "
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"séquence ou un itérable."
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#: library/statistics.rst:122
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msgid ""
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"The arithmetic mean is the sum of the data divided by the number of data "
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"points. It is commonly called \"the average\", although it is only one of "
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"many different mathematical averages. It is a measure of the central "
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"location of the data."
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msgstr ""
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"La moyenne arithmétique est la somme des valeurs divisée par le nombre "
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"d'observations. Il s'agit de la valeur couramment désignée comme la "
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"« moyenne » bien qu'il existe de multiples façons de définir "
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"mathématiquement la moyenne. C'est une mesure de la tendance centrale des "
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"données."
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#: library/statistics.rst:127
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msgid "If *data* is empty, :exc:`StatisticsError` will be raised."
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msgstr "Une erreur :exc:`StatisticsError` est levée si *data* est vide."
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#: library/statistics.rst:129
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msgid "Some examples of use:"
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msgstr "Exemples d'utilisation :"
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#: library/statistics.rst:148
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#, fuzzy
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msgid ""
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"The mean is strongly affected by `outliers <https://en.wikipedia.org/wiki/"
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"Outlier>`_ and is not necessarily a typical example of the data points. For "
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"a more robust, although less efficient, measure of `central tendency "
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"<https://en.wikipedia.org/wiki/Central_tendency>`_, see :func:`median`."
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msgstr ""
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"La moyenne arithmétique est fortement impactée par la présence de valeurs "
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"aberrantes et n'est pas un estimateur robuste de la tendance centrale : la "
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"moyenne n'est pas nécessairement un exemple représentatif de l'échantillon. "
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"Voir :func:`median` et :func:`mode` pour des mesures plus robustes de la "
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"tendance centrale."
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#: library/statistics.rst:154
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msgid ""
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"The sample mean gives an unbiased estimate of the true population mean, so "
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"that when taken on average over all the possible samples, ``mean(sample)`` "
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"converges on the true mean of the entire population. If *data* represents "
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"the entire population rather than a sample, then ``mean(data)`` is "
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"equivalent to calculating the true population mean μ."
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msgstr ""
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"La moyenne de l'échantillon est une estimation non biaisée de la moyenne de "
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"la véritable population. Ainsi, en calculant la moyenne sur tous les "
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"échantillons possibles, ``mean(sample)`` converge vers la moyenne réelle de "
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"la population entière. Si *data* est une population entière plutôt qu'un "
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"échantillon, alors ``mean(data)`` équivaut à calculer la véritable moyenne μ."
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#: library/statistics.rst:163
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msgid "Convert *data* to floats and compute the arithmetic mean."
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msgstr ""
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"Convertit *data* en nombres à virgule flottante et calcule la moyenne "
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"arithmétique."
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#: library/statistics.rst:165
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msgid ""
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"This runs faster than the :func:`mean` function and it always returns a :"
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"class:`float`. The *data* may be a sequence or iterable. If the input "
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"dataset is empty, raises a :exc:`StatisticsError`."
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msgstr ""
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"Cette fonction est plus rapide que :func:`mean` et renvoie toujours un :"
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"class:`float`. *data* peut être une séquence ou un itérable. Si les données "
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"d'entrée sont vides, la fonction lève une erreur :exc:`StatisticsError`."
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#: library/statistics.rst:174
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msgid ""
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"Optional weighting is supported. For example, a professor assigns a grade "
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"for a course by weighting quizzes at 20%, homework at 20%, a midterm exam at "
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"30%, and a final exam at 30%:"
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msgstr ""
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#: library/statistics.rst:185
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msgid ""
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"If *weights* is supplied, it must be the same length as the *data* or a :exc:"
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"`ValueError` will be raised."
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msgstr ""
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#: library/statistics.rst:258
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msgid "Added support for *weights*."
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msgstr ""
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#: library/statistics.rst:196
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msgid "Convert *data* to floats and compute the geometric mean."
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msgstr ""
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"Convertit *data* en nombres à virgule flottante et calcule la moyenne "
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"géométrique."
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#: library/statistics.rst:198
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msgid ""
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"The geometric mean indicates the central tendency or typical value of the "
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"*data* using the product of the values (as opposed to the arithmetic mean "
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"which uses their sum)."
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msgstr ""
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"La moyenne géométrique mesure la tendance centrale ou la valeur typique de "
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"*data* en utilisant le produit des valeurs (par opposition à la moyenne "
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"arithmétique qui utilise la somme)."
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#: library/statistics.rst:202
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msgid ""
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"Raises a :exc:`StatisticsError` if the input dataset is empty, if it "
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"contains a zero, or if it contains a negative value. The *data* may be a "
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"sequence or iterable."
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msgstr ""
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"Lève une erreur :exc:`StatisticsError` si les données sont vides, si elles "
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"contiennent un zéro ou une valeur négative. *data* peut être une séquence ou "
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"un itérable."
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#: library/statistics.rst:206
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msgid ""
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"No special efforts are made to achieve exact results. (However, this may "
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"change in the future.)"
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msgstr ""
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"Aucune mesure particulière n'est prise pour garantir que le résultat est "
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"parfaitement exact (cela peut toutefois changer dans une version future)."
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#: library/statistics.rst:219
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#, fuzzy
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msgid ""
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"Return the harmonic mean of *data*, a sequence or iterable of real-valued "
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"numbers. If *weights* is omitted or *None*, then equal weighting is assumed."
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msgstr ""
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"Renvoie la moyenne harmonique de *data*, une séquence ou un itérable de "
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"nombres réels."
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#: library/statistics.rst:223
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#, fuzzy
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msgid ""
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"The harmonic mean is the reciprocal of the arithmetic :func:`mean` of the "
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"reciprocals of the data. For example, the harmonic mean of three values *a*, "
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"*b* and *c* will be equivalent to ``3/(1/a + 1/b + 1/c)``. If one of the "
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"values is zero, the result will be zero."
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msgstr ""
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"La moyenne harmonique est l'inverse de la moyenne arithmétique :func:`mean` "
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"des inverses. Par exemple, la moyenne harmonique de trois valeurs *a*, *b* "
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"et *c* vaut ``3/(1/a + 1/b + 1/c)``. Si une des valeurs est nulle, alors le "
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"résultat est zéro."
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#: library/statistics.rst:228
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#, fuzzy
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msgid ""
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"The harmonic mean is a type of average, a measure of the central location of "
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"the data. It is often appropriate when averaging ratios or rates, for "
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"example speeds."
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msgstr ""
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"La moyenne harmonique est un type de moyenne, une mesure de la tendance "
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"centrale des données. Elle est généralement appropriée pour calculer des "
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"moyennes de taux ou de proportions, par exemple des vitesses."
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#: library/statistics.rst:232
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msgid ""
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"Suppose a car travels 10 km at 40 km/hr, then another 10 km at 60 km/hr. "
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"What is the average speed?"
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msgstr ""
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"Supposons qu'une voiture parcoure 10 km à 40 km/h puis 10 km à 60 km/h. "
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"Quelle a été sa vitesse moyenne ?"
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#: library/statistics.rst:240
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#, fuzzy
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msgid ""
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"Suppose a car travels 40 km/hr for 5 km, and when traffic clears, speeds-up "
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"to 60 km/hr for the remaining 30 km of the journey. What is the average "
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"speed?"
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msgstr ""
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"Supposons qu'une voiture parcoure 10 km à 40 km/h puis 10 km à 60 km/h. "
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"Quelle a été sa vitesse moyenne ?"
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#: library/statistics.rst:249
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#, fuzzy
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msgid ""
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":exc:`StatisticsError` is raised if *data* is empty, any element is less "
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"than zero, or if the weighted sum isn't positive."
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msgstr ""
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"Une erreur :exc:`StatisticsError` est levée si *data* est vide ou si l'un de "
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"ses éléments est inférieur à zéro."
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#: library/statistics.rst:252
|
||
msgid ""
|
||
"The current algorithm has an early-out when it encounters a zero in the "
|
||
"input. This means that the subsequent inputs are not tested for validity. "
|
||
"(This behavior may change in the future.)"
|
||
msgstr ""
|
||
"L'algorithme actuellement implémenté s'arrête prématurément lors de la "
|
||
"rencontre d'un zéro dans le parcours de l'entrée. Cela signifie que la "
|
||
"validité des valeurs suivantes n'est pas testée (ce comportement est "
|
||
"susceptible de changer dans une version future)."
|
||
|
||
#: library/statistics.rst:263
|
||
msgid ""
|
||
"Return the median (middle value) of numeric data, using the common \"mean of "
|
||
"middle two\" method. If *data* is empty, :exc:`StatisticsError` is raised. "
|
||
"*data* can be a sequence or iterable."
|
||
msgstr ""
|
||
"Renvoie la médiane (la valeur centrale) de données numériques en utilisant "
|
||
"la méthode classique « moyenne des deux du milieu ». Lève une erreur :exc:"
|
||
"`StatisticsError` si *data* est vide. *data* peut être une séquence ou un "
|
||
"itérable."
|
||
|
||
#: library/statistics.rst:267
|
||
msgid ""
|
||
"The median is a robust measure of central location and is less affected by "
|
||
"the presence of outliers. When the number of data points is odd, the middle "
|
||
"data point is returned:"
|
||
msgstr ""
|
||
"La médiane est une mesure robuste de la tendance centrale et est moins "
|
||
"sensible à la présence de valeurs aberrantes que la moyenne. Lorsque le "
|
||
"nombre d'observations est impair, la valeur du milieu est renvoyée :"
|
||
|
||
#: library/statistics.rst:276
|
||
msgid ""
|
||
"When the number of data points is even, the median is interpolated by taking "
|
||
"the average of the two middle values:"
|
||
msgstr ""
|
||
"Lorsque le nombre d'observations est pair, la médiane est interpolée en "
|
||
"calculant la moyenne des deux valeurs du milieu :"
|
||
|
||
#: library/statistics.rst:284
|
||
msgid ""
|
||
"This is suited for when your data is discrete, and you don't mind that the "
|
||
"median may not be an actual data point."
|
||
msgstr ""
|
||
"Cette approche est adaptée à des données discrètes à condition que vous "
|
||
"acceptiez que la médiane ne fasse pas nécessairement partie des observations."
|
||
|
||
#: library/statistics.rst:287
|
||
msgid ""
|
||
"If the data is ordinal (supports order operations) but not numeric (doesn't "
|
||
"support addition), consider using :func:`median_low` or :func:`median_high` "
|
||
"instead."
|
||
msgstr ""
|
||
"Si les données sont ordinales (elles peuvent être ordonnées) mais pas "
|
||
"numériques (elles ne peuvent être additionnées), utilisez :func:`median_low` "
|
||
"ou :func:`median_high` à la place."
|
||
|
||
#: library/statistics.rst:293
|
||
msgid ""
|
||
"Return the low median of numeric data. If *data* is empty, :exc:"
|
||
"`StatisticsError` is raised. *data* can be a sequence or iterable."
|
||
msgstr ""
|
||
"Renvoie la médiane basse de données numériques. Lève une erreur :exc:"
|
||
"`StatisticsError` si *data* est vide. *data* peut être une séquence ou un "
|
||
"itérable."
|
||
|
||
#: library/statistics.rst:296
|
||
msgid ""
|
||
"The low median is always a member of the data set. When the number of data "
|
||
"points is odd, the middle value is returned. When it is even, the smaller "
|
||
"of the two middle values is returned."
|
||
msgstr ""
|
||
"La médiane basse est toujours une valeur représentée dans les données. "
|
||
"Lorsque le nombre d'observations est impair, la valeur du milieu est "
|
||
"renvoyée. Sinon, la plus petite des deux valeurs du milieu est renvoyée."
|
||
|
||
#: library/statistics.rst:307
|
||
msgid ""
|
||
"Use the low median when your data are discrete and you prefer the median to "
|
||
"be an actual data point rather than interpolated."
|
||
msgstr ""
|
||
"Utilisez la médiane basse lorsque vos données sont discrètes et que vous "
|
||
"préférez que la médiane soit une valeur représentée dans vos observations "
|
||
"plutôt que le résultat d'une interpolation."
|
||
|
||
#: library/statistics.rst:313
|
||
msgid ""
|
||
"Return the high median of data. If *data* is empty, :exc:`StatisticsError` "
|
||
"is raised. *data* can be a sequence or iterable."
|
||
msgstr ""
|
||
"Renvoie la médiane haute des données. Lève une erreur :exc:`StatisticsError` "
|
||
"si *data* est vide. *data* peut être une séquence ou un itérable."
|
||
|
||
#: library/statistics.rst:316
|
||
msgid ""
|
||
"The high median is always a member of the data set. When the number of data "
|
||
"points is odd, the middle value is returned. When it is even, the larger of "
|
||
"the two middle values is returned."
|
||
msgstr ""
|
||
"La médiane haute est toujours une valeur représentée dans les données. "
|
||
"Lorsque le nombre d'observations est impair, la valeur du milieu est "
|
||
"renvoyée. Sinon, la plus grande des deux valeurs du milieu est renvoyée."
|
||
|
||
#: library/statistics.rst:327
|
||
msgid ""
|
||
"Use the high median when your data are discrete and you prefer the median to "
|
||
"be an actual data point rather than interpolated."
|
||
msgstr ""
|
||
"Utilisez la médiane haute lorsque vos données sont discrètes et que vous "
|
||
"préférez que la médiane soit une valeur représentée dans vos observations "
|
||
"plutôt que le résultat d'une interpolation."
|
||
|
||
#: library/statistics.rst:333
|
||
msgid ""
|
||
"Return the median of grouped continuous data, calculated as the 50th "
|
||
"percentile, using interpolation. If *data* is empty, :exc:`StatisticsError` "
|
||
"is raised. *data* can be a sequence or iterable."
|
||
msgstr ""
|
||
"Renvoie la médiane de données réelles groupées, calculée comme le 50\\ :sup:"
|
||
"`e` percentile (avec interpolation). Lève une erreur :exc:`StatisticsError` "
|
||
"si *data* est vide. *data* peut être une séquence ou un itérable."
|
||
|
||
#: library/statistics.rst:342
|
||
msgid ""
|
||
"In the following example, the data are rounded, so that each value "
|
||
"represents the midpoint of data classes, e.g. 1 is the midpoint of the class "
|
||
"0.5--1.5, 2 is the midpoint of 1.5--2.5, 3 is the midpoint of 2.5--3.5, "
|
||
"etc. With the data given, the middle value falls somewhere in the class "
|
||
"3.5--4.5, and interpolation is used to estimate it:"
|
||
msgstr ""
|
||
"Dans l'exemple ci-dessous, les valeurs sont arrondies de sorte que chaque "
|
||
"valeur représente le milieu d'un groupe. Par exemple 1 est le milieu du "
|
||
"groupe 0,5 - 1, 2 est le milieu du groupe 1,5 - 2,5, 3 est le milieu de 2,5 -"
|
||
" 3,5, etc. Compte-tenu des valeurs ci-dessous, la valeur centrale se situe "
|
||
"quelque part dans le groupe 3,5 - 4,5 et est estimée par interpolation :"
|
||
|
||
#: library/statistics.rst:353
|
||
msgid ""
|
||
"Optional argument *interval* represents the class interval, and defaults to "
|
||
"1. Changing the class interval naturally will change the interpolation:"
|
||
msgstr ""
|
||
"L'argument optionnel *interval* représente la largeur de l'intervalle des "
|
||
"groupes (par défaut, 1). Changer l'intervalle des groupes change bien sûr "
|
||
"l'interpolation :"
|
||
|
||
#: library/statistics.rst:363
|
||
msgid ""
|
||
"This function does not check whether the data points are at least *interval* "
|
||
"apart."
|
||
msgstr ""
|
||
"Cette fonction ne vérifie pas que les valeurs sont bien séparées d'au moins "
|
||
"une fois *interval*."
|
||
|
||
#: library/statistics.rst:368
|
||
msgid ""
|
||
"Under some circumstances, :func:`median_grouped` may coerce data points to "
|
||
"floats. This behaviour is likely to change in the future."
|
||
msgstr ""
|
||
"Sous certaines conditions, :func:`median_grouped` peut convertir les valeurs "
|
||
"en nombres à virgule flottante. Ce comportement est susceptible de changer "
|
||
"dans le futur."
|
||
|
||
#: library/statistics.rst:373
|
||
msgid ""
|
||
"\"Statistics for the Behavioral Sciences\", Frederick J Gravetter and Larry "
|
||
"B Wallnau (8th Edition)."
|
||
msgstr ""
|
||
"*Statistics for the Behavioral Sciences*, Frederick J Gravetter et Larry B "
|
||
"Wallnau (8\\ :sup:`e` édition, ouvrage en anglais)."
|
||
|
||
#: library/statistics.rst:376
|
||
msgid ""
|
||
"The `SSMEDIAN <https://help.gnome.org/users/gnumeric/stable/gnumeric."
|
||
"html#gnumeric-function-SSMEDIAN>`_ function in the Gnome Gnumeric "
|
||
"spreadsheet, including `this discussion <https://mail.gnome.org/archives/"
|
||
"gnumeric-list/2011-April/msg00018.html>`_."
|
||
msgstr ""
|
||
"La fonction `SSMEDIAN <https://help.gnome.org/users/gnumeric/stable/gnumeric."
|
||
"html#gnumeric-function-SSMEDIAN>`_ du tableur Gnome Gnumeric ainsi que "
|
||
"`cette discussion <https://mail.gnome.org/archives/gnumeric-list/2011-April/"
|
||
"msg00018.html>`_."
|
||
|
||
#: library/statistics.rst:384
|
||
msgid ""
|
||
"Return the single most common data point from discrete or nominal *data*. "
|
||
"The mode (when it exists) is the most typical value and serves as a measure "
|
||
"of central location."
|
||
msgstr ""
|
||
"Renvoie la valeur la plus représentée dans la collection *data* (discrète ou "
|
||
"nominale). Ce mode, lorsqu'il existe, est la valeur la plus représentative "
|
||
"des données et est une mesure de la tendance centrale."
|
||
|
||
#: library/statistics.rst:388
|
||
msgid ""
|
||
"If there are multiple modes with the same frequency, returns the first one "
|
||
"encountered in the *data*. If the smallest or largest of those is desired "
|
||
"instead, use ``min(multimode(data))`` or ``max(multimode(data))``. If the "
|
||
"input *data* is empty, :exc:`StatisticsError` is raised."
|
||
msgstr ""
|
||
"S'il existe plusieurs modes avec la même fréquence, cette fonction renvoie "
|
||
"le premier qui a été rencontré dans *data*. Utilisez "
|
||
"``min(multimode(data))`` ou ``max(multimode(data))`` si vous désirez le plus "
|
||
"petit mode ou le plus grand mode. Lève une erreur :exc:`StatisticsError` si "
|
||
"*data* est vide."
|
||
|
||
#: library/statistics.rst:393
|
||
msgid ""
|
||
"``mode`` assumes discrete data and returns a single value. This is the "
|
||
"standard treatment of the mode as commonly taught in schools:"
|
||
msgstr ""
|
||
"``mode`` suppose que les données sont discrètes et renvoie une seule valeur. "
|
||
"Il s'agit de la définition usuelle du mode telle qu'enseignée dans à "
|
||
"l'école :"
|
||
|
||
#: library/statistics.rst:401
|
||
msgid ""
|
||
"The mode is unique in that it is the only statistic in this package that "
|
||
"also applies to nominal (non-numeric) data:"
|
||
msgstr ""
|
||
"Le mode a la particularité d'être la seule statistique de ce module à "
|
||
"pouvoir être calculée sur des données nominales (non numériques) :"
|
||
|
||
#: library/statistics.rst:409
|
||
msgid ""
|
||
"Now handles multimodal datasets by returning the first mode encountered. "
|
||
"Formerly, it raised :exc:`StatisticsError` when more than one mode was found."
|
||
msgstr ""
|
||
"Gère désormais des jeux de données avec plusieurs modes en renvoyant le "
|
||
"premier mode rencontré. Précédemment, une erreur :exc:`StatisticsError` "
|
||
"était levée si plusieurs modes étaient trouvés."
|
||
|
||
#: library/statistics.rst:417
|
||
msgid ""
|
||
"Return a list of the most frequently occurring values in the order they were "
|
||
"first encountered in the *data*. Will return more than one result if there "
|
||
"are multiple modes or an empty list if the *data* is empty:"
|
||
msgstr ""
|
||
"Renvoie une liste des valeurs les plus fréquentes en suivant leur ordre "
|
||
"d'apparition dans *data*. Renvoie plusieurs résultats s'il y a plusieurs "
|
||
"modes ou une liste vide si *data* est vide :"
|
||
|
||
#: library/statistics.rst:433
|
||
msgid ""
|
||
"Return the population standard deviation (the square root of the population "
|
||
"variance). See :func:`pvariance` for arguments and other details."
|
||
msgstr ""
|
||
"Renvoie l'écart-type de la population (racine carrée de la variance de la "
|
||
"population). Voir :func:`pvariance` pour les arguments et d'autres "
|
||
"précisions."
|
||
|
||
#: library/statistics.rst:444
|
||
msgid ""
|
||
"Return the population variance of *data*, a non-empty sequence or iterable "
|
||
"of real-valued numbers. Variance, or second moment about the mean, is a "
|
||
"measure of the variability (spread or dispersion) of data. A large variance "
|
||
"indicates that the data is spread out; a small variance indicates it is "
|
||
"clustered closely around the mean."
|
||
msgstr ""
|
||
"Renvoie la variance de la population *data*, une séquence non-vide ou un "
|
||
"itérable de valeurs réelles. La variance, ou moment de second ordre, est une "
|
||
"mesure de la variabilité (ou dispersion) des données. Une variance élevée "
|
||
"indique une large dispersion des valeurs ; une faible variance indique que "
|
||
"les valeurs sont resserrées autour de la moyenne."
|
||
|
||
#: library/statistics.rst:450
|
||
msgid ""
|
||
"If the optional second argument *mu* is given, it is typically the mean of "
|
||
"the *data*. It can also be used to compute the second moment around a point "
|
||
"that is not the mean. If it is missing or ``None`` (the default), the "
|
||
"arithmetic mean is automatically calculated."
|
||
msgstr ""
|
||
"Si le second argument optionnel *mu* est n'est pas spécifié ou est ``None`` "
|
||
"(par défaut), il est remplacé automatiquement par la moyenne arithmétique. "
|
||
"Cet argument correspond en général à la moyenne de *data*. En le spécifiant "
|
||
"autrement, cela permet de calculer le moment de second ordre autour d'un "
|
||
"point qui n'est pas la moyenne."
|
||
|
||
#: library/statistics.rst:455
|
||
msgid ""
|
||
"Use this function to calculate the variance from the entire population. To "
|
||
"estimate the variance from a sample, the :func:`variance` function is "
|
||
"usually a better choice."
|
||
msgstr ""
|
||
"Utilisez cette fonction pour calculer la variance sur une population "
|
||
"complète. Pour estimer la variance à partir d'un échantillon, utilisez "
|
||
"plutôt :func:`variance` à la place."
|
||
|
||
#: library/statistics.rst:459
|
||
msgid "Raises :exc:`StatisticsError` if *data* is empty."
|
||
msgstr "Lève une erreur :exc:`StatisticsError` si *data* est vide."
|
||
|
||
#: library/statistics.rst:531 library/statistics.rst:663
|
||
msgid "Examples:"
|
||
msgstr "Exemples :"
|
||
|
||
#: library/statistics.rst:469
|
||
msgid ""
|
||
"If you have already calculated the mean of your data, you can pass it as the "
|
||
"optional second argument *mu* to avoid recalculation:"
|
||
msgstr ""
|
||
"Si vous connaissez la moyenne de vos données, il est possible de la passer "
|
||
"comme argument optionnel *mu* lors de l'appel de fonction pour éviter de la "
|
||
"calculer une nouvelle fois :"
|
||
|
||
#: library/statistics.rst:478
|
||
msgid "Decimals and Fractions are supported:"
|
||
msgstr "La fonction gère les nombres décimaux et les fractions :"
|
||
|
||
#: library/statistics.rst:492
|
||
msgid ""
|
||
"When called with the entire population, this gives the population variance "
|
||
"σ². When called on a sample instead, this is the biased sample variance s², "
|
||
"also known as variance with N degrees of freedom."
|
||
msgstr ""
|
||
"Cette fonction renvoie la variance de la population σ² lorsqu'elle est "
|
||
"appliquée sur la population entière. Si elle est appliquée seulement sur un "
|
||
"échantillon, le résultat est alors la variance de l'échantillon s² ou "
|
||
"variance à N degrés de liberté."
|
||
|
||
#: library/statistics.rst:496
|
||
msgid ""
|
||
"If you somehow know the true population mean μ, you may use this function to "
|
||
"calculate the variance of a sample, giving the known population mean as the "
|
||
"second argument. Provided the data points are a random sample of the "
|
||
"population, the result will be an unbiased estimate of the population "
|
||
"variance."
|
||
msgstr ""
|
||
"Si vous connaissez d'avance la vraie moyenne de la population μ, vous pouvez "
|
||
"utiliser cette fonction pour calculer la variance de l'échantillon sachant "
|
||
"la moyenne de la population en la passante comme second argument. En "
|
||
"supposant que les observations sont issues d'un tirage aléatoire uniforme "
|
||
"dans la population, le résultat sera une estimation non biaisée de la "
|
||
"variance de la population."
|
||
|
||
#: library/statistics.rst:505
|
||
msgid ""
|
||
"Return the sample standard deviation (the square root of the sample "
|
||
"variance). See :func:`variance` for arguments and other details."
|
||
msgstr ""
|
||
"Renvoie l'écart-type de l'échantillon (racine carrée de la variance de "
|
||
"l'échantillon). Voir :func:`variance` pour les arguments et plus de détails."
|
||
|
||
#: library/statistics.rst:516
|
||
msgid ""
|
||
"Return the sample variance of *data*, an iterable of at least two real-"
|
||
"valued numbers. Variance, or second moment about the mean, is a measure of "
|
||
"the variability (spread or dispersion) of data. A large variance indicates "
|
||
"that the data is spread out; a small variance indicates it is clustered "
|
||
"closely around the mean."
|
||
msgstr ""
|
||
"Renvoie la variance de l'échantillon *data*, un itérable d'au moins deux "
|
||
"valeurs réelles. La variance, ou moment de second ordre, est une mesure de "
|
||
"la variabilité (ou dispersion) des données. Une variance élevée indique que "
|
||
"les données sont très dispersées ; une variance faible indique que les "
|
||
"valeurs sont resserrées autour de la moyenne."
|
||
|
||
#: library/statistics.rst:522
|
||
msgid ""
|
||
"If the optional second argument *xbar* is given, it should be the mean of "
|
||
"*data*. If it is missing or ``None`` (the default), the mean is "
|
||
"automatically calculated."
|
||
msgstr ""
|
||
"Si le second argument optionnel *xbar* est spécifié, celui-ci doit "
|
||
"correspondre à la moyenne de *data*. S'il n'est pas spécifié ou ``None`` "
|
||
"(par défaut), la moyenne est automatiquement calculée."
|
||
|
||
#: library/statistics.rst:526
|
||
msgid ""
|
||
"Use this function when your data is a sample from a population. To calculate "
|
||
"the variance from the entire population, see :func:`pvariance`."
|
||
msgstr ""
|
||
"Utilisez cette fonction lorsque vos données forment un échantillon d'une "
|
||
"population plus grande. Pour calculer la variance d'une population complète, "
|
||
"utilisez :func:`pvariance`."
|
||
|
||
#: library/statistics.rst:529
|
||
msgid "Raises :exc:`StatisticsError` if *data* has fewer than two values."
|
||
msgstr ""
|
||
"Lève une erreur :exc:`StatisticsError` si *data* contient moins de deux "
|
||
"éléments."
|
||
|
||
#: library/statistics.rst:539
|
||
msgid ""
|
||
"If you have already calculated the mean of your data, you can pass it as the "
|
||
"optional second argument *xbar* to avoid recalculation:"
|
||
msgstr ""
|
||
"Si vous connaissez la moyenne de vos données, il est possible de la passer "
|
||
"comme argument optionnel *xbar* lors de l'appel de fonction pour éviter de "
|
||
"la calculer une nouvelle fois :"
|
||
|
||
#: library/statistics.rst:548
|
||
msgid ""
|
||
"This function does not attempt to verify that you have passed the actual "
|
||
"mean as *xbar*. Using arbitrary values for *xbar* can lead to invalid or "
|
||
"impossible results."
|
||
msgstr ""
|
||
"Cette fonction ne vérifie pas que la valeur passée dans l'argument *xbar* "
|
||
"correspond bien à la moyenne. Utiliser des valeurs arbitraires pour *xbar* "
|
||
"produit des résultats impossibles ou incorrects."
|
||
|
||
#: library/statistics.rst:552
|
||
msgid "Decimal and Fraction values are supported:"
|
||
msgstr "La fonction gère les nombres décimaux et les fractions :"
|
||
|
||
#: library/statistics.rst:566
|
||
msgid ""
|
||
"This is the sample variance s² with Bessel's correction, also known as "
|
||
"variance with N-1 degrees of freedom. Provided that the data points are "
|
||
"representative (e.g. independent and identically distributed), the result "
|
||
"should be an unbiased estimate of the true population variance."
|
||
msgstr ""
|
||
"Cela correspond à la variance s² de l'échantillon avec correction de Bessel "
|
||
"(ou variance à N-1 degrés de liberté). En supposant que les observations "
|
||
"sont représentatives de la population (c'est-à-dire indépendantes et "
|
||
"identiquement distribuées), alors le résultat est une estimation non biaisée "
|
||
"de la variance."
|
||
|
||
#: library/statistics.rst:571
|
||
msgid ""
|
||
"If you somehow know the actual population mean μ you should pass it to the :"
|
||
"func:`pvariance` function as the *mu* parameter to get the variance of a "
|
||
"sample."
|
||
msgstr ""
|
||
"Si vous connaissez d'avance la vraie moyenne μ de la population, vous "
|
||
"devriez la passer à :func:`pvariance` comme paramètre *mu* pour obtenir la "
|
||
"variance de l'échantillon."
|
||
|
||
#: library/statistics.rst:577
|
||
msgid ""
|
||
"Divide *data* into *n* continuous intervals with equal probability. Returns "
|
||
"a list of ``n - 1`` cut points separating the intervals."
|
||
msgstr ""
|
||
"Divise *data* en *n* intervalles réels de même probabilité. Renvoie une "
|
||
"liste de ``n - 1`` valeurs délimitant les intervalles (les quantiles)."
|
||
|
||
#: library/statistics.rst:580
|
||
msgid ""
|
||
"Set *n* to 4 for quartiles (the default). Set *n* to 10 for deciles. Set "
|
||
"*n* to 100 for percentiles which gives the 99 cuts points that separate "
|
||
"*data* into 100 equal sized groups. Raises :exc:`StatisticsError` if *n* is "
|
||
"not least 1."
|
||
msgstr ""
|
||
"Utilisez ``n = 4`` pour obtenir les quartiles (le défaut), ``n = 10`` pour "
|
||
"obtenir les déciles et ``n = 100`` pour obtenir les centiles (ce qui produit "
|
||
"99 valeurs qui séparent *data* en 100 groupes de même taille). Lève une "
|
||
"erreur :exc:`StatisticsError` si *n* est strictement inférieur à 1."
|
||
|
||
#: library/statistics.rst:585
|
||
msgid ""
|
||
"The *data* can be any iterable containing sample data. For meaningful "
|
||
"results, the number of data points in *data* should be larger than *n*. "
|
||
"Raises :exc:`StatisticsError` if there are not at least two data points."
|
||
msgstr ""
|
||
"*data* peut être n'importe quel itérable contenant les valeurs de "
|
||
"l'échantillon. Pour que les résultats aient un sens, le nombre "
|
||
"d'observations dans l'échantillon *data* doit être plus grand que *n*. Lève "
|
||
"une erreur :exc:`StatisticsError` s'il n'y a pas au moins deux observations."
|
||
|
||
#: library/statistics.rst:589
|
||
msgid ""
|
||
"The cut points are linearly interpolated from the two nearest data points. "
|
||
"For example, if a cut point falls one-third of the distance between two "
|
||
"sample values, ``100`` and ``112``, the cut-point will evaluate to ``104``."
|
||
msgstr ""
|
||
"Les quantiles sont linéairement interpolées à partir des deux valeurs les "
|
||
"plus proches dans l'échantillon. Par exemple, si un quantile se situe à un "
|
||
"tiers de la distance entre les deux valeurs de l'échantillon ``100`` et "
|
||
"``112``, le quantile vaudra ``104``."
|
||
|
||
#: library/statistics.rst:594
|
||
msgid ""
|
||
"The *method* for computing quantiles can be varied depending on whether the "
|
||
"*data* includes or excludes the lowest and highest possible values from the "
|
||
"population."
|
||
msgstr ""
|
||
"L'argument *method* indique la méthode à utiliser pour calculer les "
|
||
"quantiles et peut être modifié pour spécifier s'il faut inclure ou exclure "
|
||
"les valeurs basses et hautes de *data* de la population."
|
||
|
||
#: library/statistics.rst:598
|
||
msgid ""
|
||
"The default *method* is \"exclusive\" and is used for data sampled from a "
|
||
"population that can have more extreme values than found in the samples. The "
|
||
"portion of the population falling below the *i-th* of *m* sorted data points "
|
||
"is computed as ``i / (m + 1)``. Given nine sample values, the method sorts "
|
||
"them and assigns the following percentiles: 10%, 20%, 30%, 40%, 50%, 60%, "
|
||
"70%, 80%, 90%."
|
||
msgstr ""
|
||
"La valeur par défaut pour *method* est ``\"exclusive\"`` et est applicable "
|
||
"pour des données échantillonnées dans une population dont une des valeurs "
|
||
"extrêmes peut être plus grande (respectivement plus petite) que le maximum "
|
||
"(respectivement le minimum) des valeurs de l'échantillon. La proportion de "
|
||
"la population se situant en-dessous du i\\ :sup:`e` de *m* valeurs ordonnées "
|
||
"est calculée par la formule ``i / (m + 1)``. Par exemple, en supposant 9 "
|
||
"valeurs dans l'échantillon, cette méthode les ordonne et leur associe les "
|
||
"quantiles suivants : 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%."
|
||
|
||
#: library/statistics.rst:605
|
||
msgid ""
|
||
"Setting the *method* to \"inclusive\" is used for describing population data "
|
||
"or for samples that are known to include the most extreme values from the "
|
||
"population. The minimum value in *data* is treated as the 0th percentile "
|
||
"and the maximum value is treated as the 100th percentile. The portion of the "
|
||
"population falling below the *i-th* of *m* sorted data points is computed as "
|
||
"``(i - 1) / (m - 1)``. Given 11 sample values, the method sorts them and "
|
||
"assigns the following percentiles: 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, "
|
||
"80%, 90%, 100%."
|
||
msgstr ""
|
||
"En utilisant ``\"inclusive\"`` comme valeur du paramètre *method*, on "
|
||
"suppose que *data* correspond soit à une population entière, soit que les "
|
||
"valeurs extrêmes de la population sont représentées dans l'échantillon. Le "
|
||
"minimum de *data* est alors considéré comme 0\\ :sup:`e` centile et le "
|
||
"maximum comme 100\\ :sup:`e` centile. La proportion de la population se "
|
||
"situant sous la i\\ :sup:`e` valeur de *m* valeurs ordonnées est calculée "
|
||
"par la formule ``(i - 1)/(m - 1)``. En supposant que l'on a 11 valeurs dans "
|
||
"l'échantillon, cette méthode les ordonne et leur associe les quantiles "
|
||
"suivants : 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%."
|
||
|
||
#: library/statistics.rst:629
|
||
msgid ""
|
||
"Return the sample covariance of two inputs *x* and *y*. Covariance is a "
|
||
"measure of the joint variability of two inputs."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:632
|
||
msgid ""
|
||
"Both inputs must be of the same length (no less than two), otherwise :exc:"
|
||
"`StatisticsError` is raised."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:653
|
||
msgid ""
|
||
"Return the `Pearson's correlation coefficient <https://en.wikipedia.org/wiki/"
|
||
"Pearson_correlation_coefficient>`_ for two inputs. Pearson's correlation "
|
||
"coefficient *r* takes values between -1 and +1. It measures the strength and "
|
||
"direction of the linear relationship, where +1 means very strong, positive "
|
||
"linear relationship, -1 very strong, negative linear relationship, and 0 no "
|
||
"linear relationship."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:660
|
||
msgid ""
|
||
"Both inputs must be of the same length (no less than two), and need not to "
|
||
"be constant, otherwise :exc:`StatisticsError` is raised."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:678
|
||
msgid ""
|
||
"Return the slope and intercept of `simple linear regression <https://en."
|
||
"wikipedia.org/wiki/Simple_linear_regression>`_ parameters estimated using "
|
||
"ordinary least squares. Simple linear regression describes the relationship "
|
||
"between an independent variable *x* and a dependent variable *y* in terms of "
|
||
"this linear function:"
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:684
|
||
msgid "*y = slope \\* x + intercept + noise*"
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:686
|
||
msgid ""
|
||
"where ``slope`` and ``intercept`` are the regression parameters that are "
|
||
"estimated, and ``noise`` represents the variability of the data that was not "
|
||
"explained by the linear regression (it is equal to the difference between "
|
||
"predicted and actual values of the dependent variable)."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:692
|
||
msgid ""
|
||
"Both inputs must be of the same length (no less than two), and the "
|
||
"independent variable *x* cannot be constant; otherwise a :exc:"
|
||
"`StatisticsError` is raised."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:696
|
||
msgid ""
|
||
"For example, we can use the `release dates of the Monty Python films "
|
||
"<https://en.wikipedia.org/wiki/Monty_Python#Films>`_ to predict the "
|
||
"cumulative number of Monty Python films that would have been produced by "
|
||
"2019 assuming that they had kept the pace."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:710
|
||
msgid ""
|
||
"If *proportional* is true, the independent variable *x* and the dependent "
|
||
"variable *y* are assumed to be directly proportional. The data is fit to a "
|
||
"line passing through the origin. Since the *intercept* will always be 0.0, "
|
||
"the underlying linear function simplifies to:"
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:716
|
||
msgid "*y = slope \\* x + noise*"
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:720
|
||
msgid "Added support for *proportional*."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:724
|
||
msgid "Exceptions"
|
||
msgstr "Exceptions"
|
||
|
||
#: library/statistics.rst:726
|
||
msgid "A single exception is defined:"
|
||
msgstr "Une seule exception est définie :"
|
||
|
||
#: library/statistics.rst:730
|
||
msgid "Subclass of :exc:`ValueError` for statistics-related exceptions."
|
||
msgstr ""
|
||
"Sous-classe de :exc:`ValueError` pour les exceptions liées aux statistiques."
|
||
|
||
#: library/statistics.rst:734
|
||
msgid ":class:`NormalDist` objects"
|
||
msgstr "Objets :class:`NormalDist`"
|
||
|
||
#: library/statistics.rst:736
|
||
msgid ""
|
||
":class:`NormalDist` is a tool for creating and manipulating normal "
|
||
"distributions of a `random variable <http://www.stat.yale.edu/"
|
||
"Courses/1997-98/101/ranvar.htm>`_. It is a class that treats the mean and "
|
||
"standard deviation of data measurements as a single entity."
|
||
msgstr ""
|
||
":class:`NormalDist` est un outil permettant de créer et manipuler des lois "
|
||
"normales de `variables aléatoires <https://fr.wikipedia.org/wiki/"
|
||
"Variable_al%C3%A9atoire>`_. Cette classe gère la moyenne et l'écart-type "
|
||
"d'un ensemble d'observations comme une seule entité."
|
||
|
||
#: library/statistics.rst:742
|
||
msgid ""
|
||
"Normal distributions arise from the `Central Limit Theorem <https://en."
|
||
"wikipedia.org/wiki/Central_limit_theorem>`_ and have a wide range of "
|
||
"applications in statistics."
|
||
msgstr ""
|
||
"Les lois normales apparaissent dans de très nombreuses applications des "
|
||
"statistiques. Leur ubiquité découle du `théorème central limite <https://fr."
|
||
"wikipedia.org/wiki/Th%C3%A9or%C3%A8me_central_limite>`_."
|
||
|
||
#: library/statistics.rst:748
|
||
msgid ""
|
||
"Returns a new *NormalDist* object where *mu* represents the `arithmetic mean "
|
||
"<https://en.wikipedia.org/wiki/Arithmetic_mean>`_ and *sigma* represents the "
|
||
"`standard deviation <https://en.wikipedia.org/wiki/Standard_deviation>`_."
|
||
msgstr ""
|
||
"Renvoie un nouvel objet *NormalDist* où *mu* représente la `moyenne "
|
||
"arithmétique <https://fr.wikipedia.org/wiki/Moyenne_arithm%C3%A9tique>`_ et "
|
||
"*sigma* `l'écart-type <https://fr.wikipedia.org/wiki/%C3%89cart_type>`_."
|
||
|
||
#: library/statistics.rst:753
|
||
msgid "If *sigma* is negative, raises :exc:`StatisticsError`."
|
||
msgstr "Lève une erreur :exc:`StatisticsError` si *sigma* est négatif."
|
||
|
||
#: library/statistics.rst:757
|
||
msgid ""
|
||
"A read-only property for the `arithmetic mean <https://en.wikipedia.org/wiki/"
|
||
"Arithmetic_mean>`_ of a normal distribution."
|
||
msgstr ""
|
||
"Attribut en lecture seule correspondant à la `moyenne arithmétique <https://"
|
||
"fr.wikipedia.org/wiki/Moyenne_arithm%C3%A9tique>`_ d'une loi normale."
|
||
|
||
#: library/statistics.rst:763
|
||
msgid ""
|
||
"A read-only property for the `median <https://en.wikipedia.org/wiki/"
|
||
"Median>`_ of a normal distribution."
|
||
msgstr ""
|
||
"Attribut en lecture seule correspondant à la `médiane <https://fr.wikipedia."
|
||
"org/wiki/M%C3%A9diane_(statistiques)>`_ d'une loi normale."
|
||
|
||
#: library/statistics.rst:769
|
||
msgid ""
|
||
"A read-only property for the `mode <https://en.wikipedia.org/wiki/"
|
||
"Mode_(statistics)>`_ of a normal distribution."
|
||
msgstr ""
|
||
"Attribut en lecture seule correspondant au `mode <https://fr.wikipedia.org/"
|
||
"wiki/Mode_(statistiques)>`_ d'une loi normale."
|
||
|
||
#: library/statistics.rst:775
|
||
msgid ""
|
||
"A read-only property for the `standard deviation <https://en.wikipedia.org/"
|
||
"wiki/Standard_deviation>`_ of a normal distribution."
|
||
msgstr ""
|
||
"Attribut en lecture seule correspondant à `l'écart-type <https://fr."
|
||
"wikipedia.org/wiki/%C3%89cart_type>`_ d'une loi normale."
|
||
|
||
#: library/statistics.rst:781
|
||
msgid ""
|
||
"A read-only property for the `variance <https://en.wikipedia.org/wiki/"
|
||
"Variance>`_ of a normal distribution. Equal to the square of the standard "
|
||
"deviation."
|
||
msgstr ""
|
||
"Attribut en lecture seule correspondant à la `variance <https://fr.wikipedia."
|
||
"org/wiki/Variance>`_ d'une loi normale. La variance est égale au carré de "
|
||
"l'écart-type."
|
||
|
||
#: library/statistics.rst:787
|
||
msgid ""
|
||
"Makes a normal distribution instance with *mu* and *sigma* parameters "
|
||
"estimated from the *data* using :func:`fmean` and :func:`stdev`."
|
||
msgstr ""
|
||
"Crée une instance de loi normale de paramètres *mu* et *sigma* estimés à "
|
||
"partir de *data* en utilisant :func:`fmean` et :func:`stdev`."
|
||
|
||
#: library/statistics.rst:790
|
||
msgid ""
|
||
"The *data* can be any :term:`iterable` and should consist of values that can "
|
||
"be converted to type :class:`float`. If *data* does not contain at least "
|
||
"two elements, raises :exc:`StatisticsError` because it takes at least one "
|
||
"point to estimate a central value and at least two points to estimate "
|
||
"dispersion."
|
||
msgstr ""
|
||
"*data* peut être n'importe quel :term:`iterable` de valeurs pouvant être "
|
||
"converties en :class:`float`. Lève une erreur :exc:`StatisticsError` si "
|
||
"*data* ne contient pas au moins deux éléments car il faut au moins un point "
|
||
"pour estimer la moyenne et deux points pour estimer la variance."
|
||
|
||
#: library/statistics.rst:798
|
||
msgid ""
|
||
"Generates *n* random samples for a given mean and standard deviation. "
|
||
"Returns a :class:`list` of :class:`float` values."
|
||
msgstr ""
|
||
"Génère *n* valeurs aléatoires suivant une loi normale de moyenne et écart-"
|
||
"type connus. Renvoie une :class:`list` de :class:`float`."
|
||
|
||
#: library/statistics.rst:801
|
||
msgid ""
|
||
"If *seed* is given, creates a new instance of the underlying random number "
|
||
"generator. This is useful for creating reproducible results, even in a "
|
||
"multi-threading context."
|
||
msgstr ""
|
||
"Si *seed* est spécifié, sa valeur est utilisée pour initialiser une nouvelle "
|
||
"instance du générateur de nombres aléatoires. Cela permet de produire des "
|
||
"résultats reproductibles même dans un contexte de parallélisme par fils "
|
||
"d'exécution."
|
||
|
||
#: library/statistics.rst:807
|
||
msgid ""
|
||
"Using a `probability density function (pdf) <https://en.wikipedia.org/wiki/"
|
||
"Probability_density_function>`_, compute the relative likelihood that a "
|
||
"random variable *X* will be near the given value *x*. Mathematically, it is "
|
||
"the limit of the ratio ``P(x <= X < x+dx) / dx`` as *dx* approaches zero."
|
||
msgstr ""
|
||
"Calcule la vraisemblance qu'une variable aléatoire *X* soit proche de la "
|
||
"valeur *x* à partir de la `fonction de densité <https://fr.wikipedia.org/"
|
||
"wiki/Variable_al%C3%A9atoire_%C3%A0_densit%C3%A9>`_. Mathématiquement, cela "
|
||
"correspond à la limite de la fraction ``P(x <= X < x + dx) / dx`` lorsque "
|
||
"``dx`` tend vers zéro."
|
||
|
||
#: library/statistics.rst:813
|
||
#, fuzzy
|
||
msgid ""
|
||
"The relative likelihood is computed as the probability of a sample occurring "
|
||
"in a narrow range divided by the width of the range (hence the word "
|
||
"\"density\"). Since the likelihood is relative to other points, its value "
|
||
"can be greater than ``1.0``."
|
||
msgstr ""
|
||
"La vraisemblance relative est calculée comme la probabilité qu'une "
|
||
"observation appartienne à un intervalle étroit divisée par la largeur de "
|
||
"l'intervalle (d'où l'appellation « densité »). La vraisemblance étant "
|
||
"relative aux autres points, sa valeur peut être supérieure à 1,0."
|
||
|
||
#: library/statistics.rst:820
|
||
msgid ""
|
||
"Using a `cumulative distribution function (cdf) <https://en.wikipedia.org/"
|
||
"wiki/Cumulative_distribution_function>`_, compute the probability that a "
|
||
"random variable *X* will be less than or equal to *x*. Mathematically, it "
|
||
"is written ``P(X <= x)``."
|
||
msgstr ""
|
||
"Calcule la probabilité qu'une variable aléatoire *X* soit inférieure ou "
|
||
"égale à *x* à partir de la `fonction de répartition <https://fr.wikipedia."
|
||
"org/wiki/Fonction_de_r%C3%A9partition>`_. Mathématiquement, cela correspond "
|
||
"à ``P(X <= x)``."
|
||
|
||
#: library/statistics.rst:827
|
||
#, fuzzy
|
||
msgid ""
|
||
"Compute the inverse cumulative distribution function, also known as the "
|
||
"`quantile function <https://en.wikipedia.org/wiki/Quantile_function>`_ or "
|
||
"the `percent-point <https://web.archive.org/web/20190203145224/https://www."
|
||
"statisticshowto.datasciencecentral.com/inverse-distribution-function/>`_ "
|
||
"function. Mathematically, it is written ``x : P(X <= x) = p``."
|
||
msgstr ""
|
||
"Calcule l'inverse de la fonction de répartition, c'est-à-dire la `fonction "
|
||
"quantile <https://fr.wikipedia.org/wiki/Fonction_quantile>`_. "
|
||
"Mathématiquement, il s'agit de ``x : P(X <= x) = p``."
|
||
|
||
#: library/statistics.rst:833
|
||
msgid ""
|
||
"Finds the value *x* of the random variable *X* such that the probability of "
|
||
"the variable being less than or equal to that value equals the given "
|
||
"probability *p*."
|
||
msgstr ""
|
||
"Détermine la valeur *x* de la variable aléatoire *X* telle que la "
|
||
"probabilité que la variable soit inférieure ou égale à cette valeur *x* est "
|
||
"égale à *p*."
|
||
|
||
#: library/statistics.rst:839
|
||
msgid ""
|
||
"Measures the agreement between two normal probability distributions. Returns "
|
||
"a value between 0.0 and 1.0 giving `the overlapping area for the two "
|
||
"probability density functions <https://www.rasch.org/rmt/rmt101r.htm>`_."
|
||
msgstr ""
|
||
"Mesure le recouvrement entre deux lois normales. Renvoie une valeur réelle "
|
||
"entre 0 et 1 indiquant `l'aire du recouvrement de deux densités de "
|
||
"probabilité <https://www.rasch.org/rmt/rmt101r.htm>`_."
|
||
|
||
#: library/statistics.rst:846
|
||
msgid ""
|
||
"Divide the normal distribution into *n* continuous intervals with equal "
|
||
"probability. Returns a list of (n - 1) cut points separating the intervals."
|
||
msgstr ""
|
||
"Divise la loi normale entre *n* intervalles réels équiprobables. Renvoie une "
|
||
"liste de ``(n - 1)`` quantiles séparant les intervalles."
|
||
|
||
#: library/statistics.rst:850
|
||
msgid ""
|
||
"Set *n* to 4 for quartiles (the default). Set *n* to 10 for deciles. Set "
|
||
"*n* to 100 for percentiles which gives the 99 cuts points that separate the "
|
||
"normal distribution into 100 equal sized groups."
|
||
msgstr ""
|
||
"Utilisez ``n = 4`` pour obtenir les quartiles (le défaut), ``n = 10`` pour "
|
||
"obtenir les déciles et ``n = 100`` pour obtenir les centiles (ce qui produit "
|
||
"99 valeurs qui séparent *data* en 100 groupes de même taille)."
|
||
|
||
#: library/statistics.rst:856
|
||
msgid ""
|
||
"Compute the `Standard Score <https://www.statisticshowto.com/probability-and-"
|
||
"statistics/z-score/>`_ describing *x* in terms of the number of standard "
|
||
"deviations above or below the mean of the normal distribution: ``(x - "
|
||
"mean) / stdev``."
|
||
msgstr ""
|
||
|
||
#: library/statistics.rst:864
|
||
msgid ""
|
||
"Instances of :class:`NormalDist` support addition, subtraction, "
|
||
"multiplication and division by a constant. These operations are used for "
|
||
"translation and scaling. For example:"
|
||
msgstr ""
|
||
"Les instances de la classe :class:`NormalDist` gèrent l'addition, la "
|
||
"soustraction, la multiplication et la division par une constante. Ces "
|
||
"opérations peuvent être utilisées pour la translation ou la mise à "
|
||
"l'échelle, par exemple :"
|
||
|
||
#: library/statistics.rst:874
|
||
msgid ""
|
||
"Dividing a constant by an instance of :class:`NormalDist` is not supported "
|
||
"because the result wouldn't be normally distributed."
|
||
msgstr ""
|
||
"Diviser une constante par une instance de :class:`NormalDist` n'est pas pris "
|
||
"en charge car le résultat ne serait pas une loi normale."
|
||
|
||
#: library/statistics.rst:877
|
||
msgid ""
|
||
"Since normal distributions arise from additive effects of independent "
|
||
"variables, it is possible to `add and subtract two independent normally "
|
||
"distributed random variables <https://en.wikipedia.org/wiki/"
|
||
"Sum_of_normally_distributed_random_variables>`_ represented as instances of :"
|
||
"class:`NormalDist`. For example:"
|
||
msgstr ""
|
||
"Étant donné que les lois normales sont issues des propriétés additives de "
|
||
"variables indépendantes, il est possible `d'ajouter ou de soustraite deux "
|
||
"variables normales indépendantes <https://en.wikipedia.org/wiki/"
|
||
"Sum_of_normally_distributed_random_variables>`_ représentées par des "
|
||
"instances de :class:`NormalDist`. Par exemple :"
|
||
|
||
#: library/statistics.rst:897
|
||
msgid ":class:`NormalDist` Examples and Recipes"
|
||
msgstr "Exemples d'utilisation de :class:`NormalDist`"
|
||
|
||
#: library/statistics.rst:899
|
||
msgid ":class:`NormalDist` readily solves classic probability problems."
|
||
msgstr ""
|
||
":class:`NormalDist` permet de résoudre aisément des problèmes probabilistes "
|
||
"classiques."
|
||
|
||
#: library/statistics.rst:901
|
||
msgid ""
|
||
"For example, given `historical data for SAT exams <https://nces.ed.gov/"
|
||
"programs/digest/d17/tables/dt17_226.40.asp>`_ showing that scores are "
|
||
"normally distributed with a mean of 1060 and a standard deviation of 195, "
|
||
"determine the percentage of students with test scores between 1100 and 1200, "
|
||
"after rounding to the nearest whole number:"
|
||
msgstr ""
|
||
"Par exemple, sachant que les `scores aux examens SAT <https://nces.ed.gov/"
|
||
"programs/digest/d17/tables/dt17_226.40.asp>`_ suivent une loi normale de "
|
||
"moyenne 1060 et d'écart-type 195, déterminer le pourcentage d'étudiants dont "
|
||
"les scores se situent entre 1100 et 1200, arrondi à l'entier le plus proche :"
|
||
|
||
#: library/statistics.rst:914
|
||
msgid ""
|
||
"Find the `quartiles <https://en.wikipedia.org/wiki/Quartile>`_ and `deciles "
|
||
"<https://en.wikipedia.org/wiki/Decile>`_ for the SAT scores:"
|
||
msgstr ""
|
||
"Déterminer les `quartiles <https://fr.wikipedia.org/wiki/Quartile>`_ et les "
|
||
"`déciles <https://fr.wikipedia.org/wiki/Decile>`_ des scores SAT :"
|
||
|
||
#: library/statistics.rst:924
|
||
msgid ""
|
||
"To estimate the distribution for a model than isn't easy to solve "
|
||
"analytically, :class:`NormalDist` can generate input samples for a `Monte "
|
||
"Carlo simulation <https://en.wikipedia.org/wiki/Monte_Carlo_method>`_:"
|
||
msgstr ""
|
||
":class:`NormalDist` peut générer des observations pour une simulation "
|
||
"utilisant la `méthode de Monte-Carlo <https://fr.wikipedia.org/wiki/"
|
||
"M%C3%A9thode_de_Monte-Carlo>`_ afin d'estimer la distribution d'un modèle "
|
||
"difficile à résoudre analytiquement :"
|
||
|
||
#: library/statistics.rst:940
|
||
#, fuzzy
|
||
msgid ""
|
||
"Normal distributions can be used to approximate `Binomial distributions "
|
||
"<https://mathworld.wolfram.com/BinomialDistribution.html>`_ when the sample "
|
||
"size is large and when the probability of a successful trial is near 50%."
|
||
msgstr ""
|
||
"Les lois normales peuvent être utilisées pour approcher des `lois binomiales "
|
||
"<https://fr.wikipedia.org/wiki/Loi_binomiale>`_ lorsque le nombre "
|
||
"d'observations est grand et que la probabilité de succès de l'épreuve est "
|
||
"proche de 50%."
|
||
|
||
#: library/statistics.rst:945
|
||
msgid ""
|
||
"For example, an open source conference has 750 attendees and two rooms with "
|
||
"a 500 person capacity. There is a talk about Python and another about Ruby. "
|
||
"In previous conferences, 65% of the attendees preferred to listen to Python "
|
||
"talks. Assuming the population preferences haven't changed, what is the "
|
||
"probability that the Python room will stay within its capacity limits?"
|
||
msgstr ""
|
||
"Par exemple, 750 personnes assistent à une conférence sur le logiciel "
|
||
"libre. Il y a deux salles pouvant chacune accueillir 500 personnes. Dans la "
|
||
"première salle a lieu une présentation sur Python, dans l'autre une "
|
||
"présentation à propos de Ruby. Lors des conférences passées, 65% des "
|
||
"personnes ont préféré écouter les présentations sur Python. En supposant que "
|
||
"les préférences de la population n'ont pas changé, quelle est la probabilité "
|
||
"que la salle Python reste en-dessous de sa capacité d'accueil ?"
|
||
|
||
#: library/statistics.rst:976
|
||
msgid "Normal distributions commonly arise in machine learning problems."
|
||
msgstr "Les lois normales interviennent souvent en apprentissage automatique."
|
||
|
||
#: library/statistics.rst:978
|
||
#, fuzzy
|
||
msgid ""
|
||
"Wikipedia has a `nice example of a Naive Bayesian Classifier <https://en."
|
||
"wikipedia.org/wiki/Naive_Bayes_classifier#Person_classification>`_. The "
|
||
"challenge is to predict a person's gender from measurements of normally "
|
||
"distributed features including height, weight, and foot size."
|
||
msgstr ""
|
||
"Wikipédia détaille un `bon exemple de classification naïve bayésienne "
|
||
"<https://fr.wikipedia.org/wiki/"
|
||
"Classification_na%C3%AFve_bay%C3%A9sienne#Classification_des_sexes>`_. "
|
||
"L'objectif est de prédire le sexe d'une personne à partir de "
|
||
"caractéristiques physiques qui suivent une loi normale, telles que la "
|
||
"hauteur, le poids et la pointure."
|
||
|
||
#: library/statistics.rst:983
|
||
msgid ""
|
||
"We're given a training dataset with measurements for eight people. The "
|
||
"measurements are assumed to be normally distributed, so we summarize the "
|
||
"data with :class:`NormalDist`:"
|
||
msgstr ""
|
||
"Nous avons à notre disposition un jeu de données d'apprentissage contenant "
|
||
"les mesures de huit personnes. On suppose que ces mesures suivent une loi "
|
||
"normale. Nous pouvons donc synthétiser les données à l'aide de :class:"
|
||
"`NormalDist` :"
|
||
|
||
#: library/statistics.rst:996
|
||
msgid ""
|
||
"Next, we encounter a new person whose feature measurements are known but "
|
||
"whose gender is unknown:"
|
||
msgstr ""
|
||
"Ensuite, nous rencontrons un nouvel individu dont nous connaissons les "
|
||
"proportions mais pas le sexe :"
|
||
|
||
#: library/statistics.rst:1005
|
||
msgid ""
|
||
"Starting with a 50% `prior probability <https://en.wikipedia.org/wiki/"
|
||
"Prior_probability>`_ of being male or female, we compute the posterior as "
|
||
"the prior times the product of likelihoods for the feature measurements "
|
||
"given the gender:"
|
||
msgstr ""
|
||
"En partant d'une `probabilité a priori <https://fr.wikipedia.org/wiki/"
|
||
"Th%C3%A9or%C3%A8me_de_Bayes>`_ de 50% d'être un homme ou une femme, nous "
|
||
"calculons la probabilité a posteriori comme le produit de la probabilité "
|
||
"antérieure et de la vraisemblance des différentes mesures étant donné le "
|
||
"sexe :"
|
||
|
||
#: library/statistics.rst:1020
|
||
msgid ""
|
||
"The final prediction goes to the largest posterior. This is known as the "
|
||
"`maximum a posteriori <https://en.wikipedia.org/wiki/"
|
||
"Maximum_a_posteriori_estimation>`_ or MAP:"
|
||
msgstr ""
|
||
"La prédiction finale est celle qui a la plus grande probabilité a "
|
||
"posteriori. Cette approche est appelée `maximum a posteriori <https://fr."
|
||
"wikipedia.org/wiki/Maximum_a_posteriori>`_ ou MAP :"
|
||
|
||
#~ msgid ""
|
||
#~ "Suppose an investor purchases an equal value of shares in each of three "
|
||
#~ "companies, with P/E (price/earning) ratios of 2.5, 3 and 10. What is the "
|
||
#~ "average P/E ratio for the investor's portfolio?"
|
||
#~ msgstr ""
|
||
#~ "Supposons qu'un investisseur achète autant de parts dans trois compagnies "
|
||
#~ "chacune de ratio cours sur bénéfices (*P/E*) 2,5, 3 et 10. Quel est le "
|
||
#~ "ratio cours sur bénéfices moyen du portefeuille de l'investisseur ?"
|