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Add translations of
library/statistics.po (#465)
* Add translations of covariance, correlation and linear_regression * Update library/statistics.po Co-authored-by: Wei-Hsiang (Matt) Wang <[email protected]> * Update library/statistics.po Co-authored-by: Wei-Hsiang (Matt) Wang <[email protected]> * Update library/statistics.po Co-authored-by: Wei-Hsiang (Matt) Wang <[email protected]> --------- Co-authored-by: Wei-Hsiang (Matt) Wang <[email protected]>
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|---|---|---|
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@@ -9,7 +9,7 @@ msgstr "" | |
| "Project-Id-Version: Python 3.11\n" | ||
| "Report-Msgid-Bugs-To: \n" | ||
| "POT-Creation-Date: 2023-05-03 00:17+0000\n" | ||
| "PO-Revision-Date: 2023-07-09 21:14+0800\n" | ||
| "PO-Revision-Date: 2023-07-10 23:56+0800\n" | ||
| "Last-Translator: Adrian Liaw <[email protected]>\n" | ||
| "Language-Team: Chinese - TAIWAN (https://github.com/python/python-docs-zh-" | ||
| "tw)\n" | ||
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@@ -251,7 +251,7 @@ msgstr ":func:`linear_regression`" | |
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| #: ../../library/statistics.rst:108 | ||
| msgid "Slope and intercept for simple linear regression." | ||
| msgstr "簡單線性回歸的斜率和截距。" | ||
| msgstr "簡單線性迴歸的斜率和截距。" | ||
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| #: ../../library/statistics.rst:113 | ||
| msgid "Function details" | ||
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@@ -864,8 +864,8 @@ msgid "" | |
| "them and assigns the following percentiles: 10%, 20%, 30%, 40%, 50%, 60%, " | ||
| "70%, 80%, 90%." | ||
| msgstr "" | ||
| "預設的 *method* 是 \"exclusive\"，用於從可能找到比樣本更極端的值的母體中抽樣的" | ||
| "樣本資料。對於 *m* 個已排序的資料點，計算出低於 *i-th* 的部分為 ``i / (m + " | ||
| "預設的 *method* 是 \"exclusive\"，用於從可能找到比樣本更極端的值的母體中抽樣" | ||
| "的樣本資料。對於 *m* 個已排序的資料點，計算出低於 *i-th* 的部分為 ``i / (m + " | ||
| "1)``。給定九個樣本資料，此方法將對資料排序且計算下列百分位數：10%、20%、30%、" | ||
| "40%、50%、60%、70%、80%、90%。" | ||
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@@ -880,23 +880,26 @@ msgid "" | |
| "assigns the following percentiles: 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, " | ||
| "80%, 90%, 100%." | ||
| msgstr "" | ||
| "若將 *method* 設為 \"inclusive\"，則用於描述母體或者已知包含母體中最極端值的樣" | ||
| "本資料。在 *data* 中的最小值被視為第 0 百分位數，最大值為第 100 百分位數。對" | ||
| "於 *m* 個已排序的資料點，計算出低於 *i-th* 的部分為 ``(i - 1) / (m - 1)``。給" | ||
| "定十一個個樣本資料，此方法將對資料排序且計算下列百分位數：0%、10%、20%、30%、" | ||
| "40%、50%、60%、70%、80%、90%、100%。" | ||
| "若將 *method* 設為 \"inclusive\"，則用於描述母體或者已知包含母體中最極端值的" | ||
| "樣本資料。在 *data* 中的最小值被視為第 0 百分位數，最大值為第 100 百分位數。" | ||
| "對於 *m* 個已排序的資料點，計算出低於 *i-th* 的部分為 ``(i - 1) / (m - 1)``。" | ||
| "給定十一個個樣本資料，此方法將對資料排序且計算下列百分位數：0%、10%、20%、" | ||
| "30%、40%、50%、60%、70%、80%、90%、100%。" | ||
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| #: ../../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 "" | ||
| "回傳兩輸入 *x* 與 *y* 的樣本共變異數 (sample covariance)。共變異數是衡量兩輸" | ||
| "入的聯合變異性 (joint variability) 的指標。" | ||
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| #: ../../library/statistics.rst:632 | ||
| msgid "" | ||
| "Both inputs must be of the same length (no less than two), otherwise :exc:" | ||
| "`StatisticsError` is raised." | ||
| msgstr "" | ||
| "兩輸入必須具有相同長度（至少兩個），否則會引發 :exc:`StatisticsError`。" | ||
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| #: ../../library/statistics.rst:653 | ||
| msgid "" | ||
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@@ -907,12 +910,18 @@ msgid "" | |
| "linear relationship, -1 very strong, negative linear relationship, and 0 no " | ||
| "linear relationship." | ||
| msgstr "" | ||
| "回傳兩輸入的 `Pearson 相關係數 (Pearson’s correlation coefficient) <https://" | ||
| "en.wikipedia.org/wiki/Pearson_correlation_coefficient>`。Pearson 相關係數 " | ||
| "*r* 的值介於 -1 與 +1 之間。它衡量線性關係的強度與方向，其中 +1 表示強烈正線" | ||
| "性相關，-1 表示強烈負線性相關，而 0 表示無線性關係。" | ||
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| #: ../../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 "" | ||
| "兩輸入必須具有相同長度（至少兩個），且不須為常數，否則會引發 :exc:" | ||
| "`StatisticsError`。" | ||
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| #: ../../library/statistics.rst:678 | ||
| msgid "" | ||
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@@ -922,6 +931,11 @@ msgid "" | |
| "between an independent variable *x* and a dependent variable *y* in terms of " | ||
| "this linear function:" | ||
| msgstr "" | ||
| "回傳使用普通最小平方法 (ordinary least square) 估計出的\\ `簡單線性迴歸 " | ||
| "(simple linear regression) <https://en.wikipedia.org/wiki/" | ||
| "Simple_linear_regression>`_ 參數中的斜率 (slope) 與截距 (intercept)。簡單線性" | ||
| "迴歸描述自變數 (independent variable) *x* 與應變數 (dependent variable) *y* " | ||
| "之間的關係，用以下的線性函式表示：" | ||
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| #: ../../library/statistics.rst:684 | ||
| msgid "*y = slope \\* x + intercept + noise*" | ||
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@@ -934,13 +948,17 @@ msgid "" | |
| "explained by the linear regression (it is equal to the difference between " | ||
| "predicted and actual values of the dependent variable)." | ||
| msgstr "" | ||
| "其中 ``slope`` 和 ``intercept`` 是被估計的迴歸參數，而 ``noise`` 表示由線性迴" | ||
| "歸未解釋的資料變異性（它等於應變數的預測值與實際值之差）。" | ||
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| #: ../../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 "" | ||
| "兩輸入必須具有相同長度（至少兩個），且自變數 *x* 不得為常數，否則會引發 :exc:" | ||
| "`StatisticsError`。" | ||
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| #: ../../library/statistics.rst:696 | ||
| msgid "" | ||
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@@ -949,6 +967,9 @@ msgid "" | |
| "cumulative number of Monty Python films that would have been produced by " | ||
| "2019 assuming that they had kept the pace." | ||
| msgstr "" | ||
| "舉例來說，我們可以使用 `Monty Python 系列電影的上映日期 <https://en." | ||
| "wikipedia.org/wiki/Monty_Python#Films>`_\\ 來預測至 2019 年為止，假設他們保持固" | ||
| "定的製作速度，應該會產生的 Monty Python 電影的累計數量。" | ||
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| #: ../../library/statistics.rst:710 | ||
| msgid "" | ||
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@@ -957,6 +978,9 @@ msgid "" | |
| "line passing through the origin. Since the *intercept* will always be 0.0, " | ||
| "the underlying linear function simplifies to:" | ||
| msgstr "" | ||
| "若將 *proportional* 設為 True，則假設自變數 *x* 與應變數" | ||
| " *y* 是直接成比例的，資料座落在通過原點的一直線上。由於 *intercept* " | ||
| "始終為 0.0，因此線性函式可簡化如下：" | ||
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| #: ../../library/statistics.rst:716 | ||
| msgid "*y = slope \\* x + noise*" | ||
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