ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

記述統計×ピアソンのカイ二乗独立性検定×
分野統計学統計学
系統Hypothesis testHypothesis test
提唱年19771900
提唱者John W. TukeyKarl Pearson
種類Summary procedureNonparametric association / goodness-of-fit
原典Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables. Philosophical Magazine, Series 5, 50(302), 157–175. link ↗
別名summary statistics, exploratory data summary, Betimsel İstatistikchi-squared test, χ² test, Ki-Kare Testi, chi-square test
関連63
概要Descriptive statistics is a set of procedures that numerically and visually summarises the essential characteristics of a dataset: central tendency (mean, median, mode), spread (standard deviation, interquartile range), shape (skewness, kurtosis), and frequency distributions. Systematised for applied data analysis by John W. Tukey in his 1977 work on Exploratory Data Analysis, descriptive statistics serves as the indispensable first step before any inferential or modelling procedure.The chi-square test of independence is a nonparametric hypothesis test that determines whether two categorical variables are statistically associated or independent of one another. Introduced by Karl Pearson in 1900, it remains the standard procedure for analysing contingency tables and requires no assumption of normality — only that observations are independent and that expected cell frequencies are sufficiently large.
ScholarGateデータセット
  1. v1
  2. 1 出典
  3. PUBLISHED
  1. v1
  2. 1 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Descriptive Statistics · Chi-square goodness-of-fit test. 2026-06-17に以下より取得 https://scholargate.app/ja/compare