STAT 111 Lecture Notes - Lecture 13: Null Hypothesis, Statistic, Alternative Hypothesis

• School: University of Vermont
• Department: Statistics
• Course: STAT 111
• Professor: Jacob William Martin

Document Summary

If it is very unusual, we have statistically significant evidence against the null hypothesis. To see if a statistic provides evidence against h0, we need to see what kind of sample statistics we would observe, just by random chance. A randomization distribution is a collection of statistics from samples simulated assuming the null hypothesis is true. The randomization distribution shows what types of statistics would be observed, just by random chance, if the null hypothesis were true. The p-value is the proportion of samples that would give a statistic as extreme as (or even more extreme) the observed sample, if the null hypothesis is true. Note that the p-value is not the probability that the null hypothesis is true. The null hypothesis is correct or incorrect. A one-sided alternative contains either > or < The p-value is the proportion in the tail in the direction specified by ha. A two-sided test requires more evidence than a one-sided test.