Statistical tests | Analysis of variance

Bartlett's test

In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. Some statistical tests, such as the analysis of variance, assume that variances are equal across groups or samples, which can be verified with Bartlett's test. In a Bartlett test, we construct the null and alternative hypothesis. For this purpose several test procedures have been devised. The test procedure due to M.S.E (Mean Square Error/Estimator) Bartlett test is represented here. This test procedure is based on the statistic whose sampling distribution is approximately a Chi-Square distribution with (k − 1) degrees of freedom, where k is the number of random samples, which may vary in size and are each drawn from independent normal distributions.Bartlett's test is sensitive to departures from normality. That is, if the samples come from non-normal distributions, then Bartlett's test may simply be testing for non-normality. Levene's test and the Brown–Forsythe test are alternatives to the Bartlett test that are less sensitive to departures from normality. (Wikipedia).

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Linear regression

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Statistics Lecture 8.2: An Introduction to Hypothesis Testing

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07 Parametric tests

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Data types

Data that are collected for statistical analysis can be classified according to their type. It is important to know what data type we are dealing with as this determines the type of statistical test to use.

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Parametric and nonparametric tests

Parametric tests are most commonly used in healthcare research. They include tests such as Student's t-test and ANOVA. There is, however a rich set of non-parametric tests that are much more appropriate to use in certain circumstances.

From playlist Learning medical statistics with python and Jupyter notebooks

Related pages

Kaiser–Meyer–Olkin test | Variance | Levene's test | Statistics | Analysis of variance | Box's M test | Sample variance | Brown–Forsythe test