Hypothesis Testing - Missouri State University

Hypothesis Testing

Applied to population parameters by specifying H0 that contains a null value for the population parameter--a value that would indicate a baseline, or that nothing of interest is happening: old news, no difference, etc.

Based on a point estimate (sample statistic), and assessing how unlikely to obtain this sample statistic if the null parameter value were correct.

Example

According to MA 115 B1 Intro Survey, 52 out of 108 students reported feeling stressed at the beginning of the semester.

What is the approximate probability to obtain the sample proportion of 48% or lower, if the true proportion of all students who feel stressed during the semester is 85%?

Hypothesis Testing

Achieving statistical significance is equivalent to rejecting the idea that the observed results are plausible if the null value is correct, i.e., rejecting the null hypothesis (H0) in a favor of alternative hypothesis (Ha).

Ha does not specify any specific value for the true population parameter.

Ha gives an open interval that may contain possible values of the true parameter, but never contains the null value.

Hypothesis Testing

H0: =0(p=p0)

Ha: >0(p>p0) upper-sided

Ha: 0(pp0) two-sided

Ha: ................
................

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