T-statistic

allows researchers to use sample data to test hypothesis with an unknown population mean, unlike the z test
standard error of mean: distance between sample and population mean
sample data can now estimate the distribution
as the sample size increases, the t-distribution approaches the z-distribution
with small df, the t distribution is smaller and more spread out
- critical values increase
on t-table, always look at the two-tailed column T hypothesis tests

state the hypothesis and select a value for a
locate the critical region
- the sample must be independent observation
  - no relationship between observations or the sample
- the underlying population from which the sample is drawn must be normal