Test statistic

Definition

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

1. Test statistics are calculated differently depending on whether you are dealing with one sample or two samples.
2. Common types of test statistics include z-scores and t-scores, which correspond to different probability distributions (normal and t-distributions).
3. The value of the test statistic determines whether to reject the null hypothesis based on a pre-determined significance level (alpha).
4. Test statistics help quantify how far your sample statistic deviates from the population parameter stated in the null hypothesis.
5. 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?

Related terms

Null Hypothesis: A statement that there is no effect or no difference, used as a starting point for statistical testing.

Significance Level (Alpha): The probability threshold below which the null hypothesis is rejected. Common values are 0.05, 0.01, and 0.10.

p-value: The probability of obtaining results at least as extreme as those observed, under the assumption that the null hypothesis is true.