# Summary

Let's wrap up this chapter.

The *t-test* and the *t-distribution* that the test is based on, are more useful when sample sizes are very small. Although the *t-test* is one of the simpler, more well-known tests, it was probably more often needed in the early twentieth century than in this age of larger (sometimes huge) datasets. Nevertheless, we may sometimes find ourselves in need of *t*. R has dedicated functions for doing *t-tests*, but it’s easy to fit linear models that produce one-sample, two-sample, and paired versions of the *t-test* in the `summary()`

table output.

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