A test statistic is a standardized value used in hypothesis testing to determine the likelihood of observing the sample data, given that the null hypothesis is true. It helps in comparing the observed data with what is expected under the null hypothesis.
5 Must Know Facts For Your Next Test
Test statistics are calculated differently depending on whether you are dealing with one sample or two samples.
Common types of test statistics include z-scores and t-scores, which correspond to different probability distributions (normal and t-distributions).
The value of the test statistic determines whether to reject the null hypothesis based on a pre-determined significance level (alpha).
Test statistics help quantify how far your sample statistic deviates from the population parameter stated in the null hypothesis.
In two-sample tests, the test statistic accounts for both sample means and their respective standard deviations.
Review Questions
What role does a test statistic play in hypothesis testing?
How do you interpret a high versus low value of a test statistic?
Why is it important to know which probability distribution corresponds to your test statistic?