Then double this probability to get the p-value. If your test statistic is positive, first find the probability that Z is greater than your test statistic (look up your test statistic on the Z-table, find its corresponding probability, and subtract it from one).
While hypothesis testing is the most common procedure for answering questions such as “are children in Samoa further from their mothers than children in Samoa?”, the use of confidence intervals or effect size measures in conjunction with hypothesis testing as a means to shed light on the phenomena discussed.
Hypothesis Testing Significance levels. The level of statistical significance is often expressed as the so-called p-value. Depending on the statistical test you have chosen, you will calculate a probability (i.e., the p-value) of observing your sample results (or more extreme) given that the null hypothesis is true.
This because in the course of a statistical test you either reject the Null-Hypothesis (and favor the Alternative Hypothesis) or you cannot reject it. Since your "goal" is to reject the Null-Hypothesis you set it to the outcome you do not want to be true.
Step 1: State Null and Alternative Hypotheses. Null Hypothesis: Population proportion of left-handed students in the College of Art and Architecture = 0.10 (p = 0.10). Alternative Hypothesis: Population proportion of left-handed students in the College of Art and Architecture > 0.10 (p > 0.10).
Step 7: Based on steps 5 and 6, draw a conclusion about H 0. If the F calculated from the data is larger than the Fα, then you are in the Rejection region and you can reject the Null Hypothesis with (1-α) level of confidence. Note that modern statistical software condenses step 6 and 7 by providing a p-value.