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- https://stats.libretexts.org/Workbench/PSYC_2200%3A_Elementary_Statistics_for_Behavioral_and_Social_Science_(Oja)_WITHOUT_UNITS/16%3A_Chi-Square/16.02%3A_Introduction_to_Goodness-of-Fit_Chi-SquareDoes your data fit the expectations? We'll see!
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/An_Introduction_to_Psychological_Statistics_(Foster_et_al.)/14%3A_Chi-square/14.02%3A_Goodness-of-FitThe first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorizatio...The first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorization was completely random. We could, in theory, also test against a specific distribution of category sizes if we have a good reason to (e.g. we have a solid foundation of how the regular population is distributed), but this is less common, so we will not deal with it in this text.
- https://stats.libretexts.org/Courses/Sacramento_City_Colllege/PSYC_330%3A_Statistics_for_the_Behavioral_Sciences_with_Dr._DeSouza/15%3A_Chi-square/15.02%3A_Goodness-of-FitThe first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorizatio...The first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorization was completely random. We could, in theory, also test against a specific distribution of category sizes if we have a good reason to (e.g. we have a solid foundation of how the regular population is distributed), but this is less common, so we will not deal with it in this text.
- https://stats.libretexts.org/Courses/Rio_Hondo_College/PSY_190%3A_Statistics_for_the_Behavioral_Sciences/14%3A_Chi-square/14.02%3A_Goodness-of-FitThe first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorizatio...The first of our two χ² tests assesses one categorical variable against a null hypothesis of equally sized frequencies. Equal frequency distributions are what we would expect to get if categorization was completely random. We could, in theory, also test against a specific distribution of category sizes if we have a good reason to (e.g. we have a solid foundation of how the regular population is distributed), but this is less common, so we will not deal with it in this text.
- https://stats.libretexts.org/Courses/Taft_College/PSYC_2200%3A_Elementary_Statistics_for_Behavioral_and_Social_Sciences_(Oja)/03%3A_Relationships/16%3A_Chi-Square/16.02%3A_Introduction_to_Goodness-of-Fit_Chi-SquareDoes your data fit the expectations? We'll see!
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_Distribution/11.08%3A_Chapter_ReviewThis page discusses the importance of the chi-square distribution in evaluating data fit, population distribution equality, event independence, and variability. It highlights the role of degrees of fr...This page discusses the importance of the chi-square distribution in evaluating data fit, population distribution equality, event independence, and variability. It highlights the role of degrees of freedom in shaping the distribution, which is right-skewed and approaches normality for df > 90.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_DistributionThis page offers a comprehensive overview of the Chi-Square Distribution, covering its characteristics and applications in hypothesis testing, including variance, goodness-of-fit, independence, and ho...This page offers a comprehensive overview of the Chi-Square Distribution, covering its characteristics and applications in hypothesis testing, including variance, goodness-of-fit, independence, and homogeneity tests. It highlights the Goodness-of-Fit test's role in evaluating data alignment with specific distributions and includes review exercises and references for further study.
