PSYC 2022 Chapter Notes - Chapter 12: Variance, Null Hypothesis, Statistical Hypothesis Testing
26 Mar 2018
School
Department
Course
Professor
Document Summary
12. 1 an overview of analysis of variance: analysis of variance, also known as anova, is a hypothesis test which is used to evaluate mean differences between two or more treatments. There is at least one mean difference among the population: type 1 errors and multiple-hypothesis tests. In anova, researchers often make a distinction between test-wise alpha levels and experimental-wise alpha levels. Instead of using the formula like we would to find mean differences in t test, we use f-ratio to find the variance between the sample mean. 12. 2 the logic of analysis variance: the analysis process divides the total variability into two components, between treatment variance, between each treatment, within-treatment variance, within each sample, between-treatment variance. It measures how much difference exists between each treatment conditions. The differences are not caused by any treatment effect but are naturally occurring. It is a result of a sampling error.
