PSY201H1 Quiz: Lecture 10 - Student's T-Test for Groups - November 29.docx
Document Summary
Lecture 10 - student"s t-test for groups t distribution is versatile! Common critical assumptions : the sampling distribution you"re estimating is normally shaped, Sage if sample size is large enough (usually >30(, thanks to clt: with mean equal to population parameter of interest. E. g. , mean, rho, difference between mean scores, sampling distribution of difference between samples: and sd equal to the matching standard error. The sampling distribution of the difference between sampling means. The distribution would result if we repeated the following 3 steps over and over again: 1. Sample n1 scores from population 1 and n2 scores from population 2: 2. Compute the means of the two samples: 3. When we can use the t distribution for independent groups. Significant difference between two independent group means: high self-esteem vs. low self-esteem, males vs. females, maximizers vs. satisficers. Sampling distribution of the mean difference is normally distributed (ok as long as n>30)
