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* the tails are thicker than for $N(0,1)$ and observations are more likely to fall within 2$\sigma$ from the mean | * the tails are thicker than for $N(0,1)$ and observations are more likely to fall within 2$\sigma$ from the mean | ||
* this is exactly the correction we need to account for poorly estimated [[Standard Error]] when the sample size is not big | * this is exactly the correction we need to account for poorly estimated [[Standard Error]] when the sample size is not big | ||
+ | |||
+ | == Alternatives to $t$-Tests == | ||
+ | * http://stats.stackexchange.com/questions/183456/have-the-reports-of-the-death-of-the-t-test-been-greatly-exaggerated | ||
$t$-tests is a family of Statistical tests that use $t$-statistics
The following tests are $t$-tests:
Assumptions for $t$ tests are similar to the assumptions of the $z$-tests
Sample Size
$t$-distribution: