The T-Test › What's Next
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This chapter covered t-tests for comparing one or two means. But what if you want to compare variances rather than means? Or compare more than two groups? The next chapters extend these ideas:
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The F-Test introduces the F-distribution for comparing variances. This is important both as a standalone test (are two groups equally variable?) and as foundation for ANOVA.
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ANOVA extends the t-test to compare three or more groups simultaneously, avoiding the multiple comparison problems that arise from running many t-tests.
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Error types, statistical power, effect sizes, and multiple comparison corrections are all essential for interpreting and designing studies that use t-tests and related methods.
The t-test you've learned here is the building block for all these extensions. Master it, and the more advanced methods will follow naturally.