PSY 350 Lecture Notes - Lecture 33: Type I And Type Ii Errors, Analysis Of Variance, Multiple Comparisons Problem
Document Summary
Include all the necessary information when writing about a t-test. Your alternative hypotheses, in conceptual terms (not symbols) The alpha level you are using and whether you are conduting a one- or a two- tailed test. Your decision: (reject or do not reject ho) Make sure you include all of the necessary information. A reader should know exactly what you did. One sample t-test: class mean to population mean (coffee) Independent samples t-test: (firstmajor)--do not enter a population mean here--shouldn"t enter one at all. Lecture 8. 3: when and why to use anova. Identify situations in which anova would be preferable. Explain the connection between multiple comparisons and the overall rate of type i error. Explain the overall logic of the anova framework. Takes the same logic and extends it so that we can compare two or more means. If you use anova to compare just 2 means, it reduces to a t-test!
