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  2. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    Residuals can be tested for homoscedasticity using the Breusch–Pagan test, [20] which performs an auxiliary regression of the squared residuals on the independent variables. From this auxiliary regression, the explained sum of squares is retained, divided by two, and then becomes the test statistic for a chi-squared distribution with the ...

  3. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    Homogeneity can be studied to several degrees of complexity. For example, considerations of homoscedasticity examine how much the variability of data-values changes throughout a dataset. However, questions of homogeneity apply to all aspects of the statistical distributions, including the location parameter

  4. Levene's test - Wikipedia

    en.wikipedia.org/wiki/Levene's_test

    It tests the null hypothesis that the population variances are equal (called homogeneity of variance or homoscedasticity). If the resulting p -value of Levene's test is less than some significance level (typically 0.05), the obtained differences in sample variances are unlikely to have occurred based on random sampling from a population with ...

  5. Regression diagnostic - Wikipedia

    en.wikipedia.org/wiki/Regression_diagnostic

    Partial regression plot Student's t test for testing inclusion of a single explanatory variable, or the F test for testing inclusion of a group of variables, both under the assumption that model errors are homoscedastic and have a normal distribution .

  6. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    The absence of homoscedasticity is called heteroscedasticity. In order to check this assumption, a plot of residuals versus predicted values (or the values of each individual predictor) can be examined for a "fanning effect" (i.e., increasing or decreasing vertical spread as one moves left to right on the plot).

  7. Cochran's C test - Wikipedia

    en.wikipedia.org/wiki/Cochran's_C_test

    Cochran's test, [1] named after William G. Cochran, is a one-sided upper limit variance outlier statistical test .The C test is used to decide if a single estimate of a variance (or a standard deviation) is significantly larger than a group of variances (or standard deviations) with which the single estimate is supposed to be comparable.

  8. Bartlett's test - Wikipedia

    en.wikipedia.org/wiki/Bartlett's_test

    In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, [1] is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. [2] Some statistical tests, such as the analysis of variance, assume that variances are equal across groups or samples, which can be checked with Bartlett's test.

  9. Goldfeld–Quandt test - Wikipedia

    en.wikipedia.org/wiki/Goldfeld–Quandt_test

    For this test, a single regression model is fitted to the complete dataset. The squares of the residuals are listed according to the order of the pre-identified explanatory variable. The test statistic used to test for homogeneity is the number of peaks in this list: ie. the count of the number of cases in which a squared residual is larger ...