Comparing Group Means: T-tests and One-way ANOVA Using Stata, SAS, R, and SPSS
Year: 2009
Type: article
Abstract: T-tests and analysis of variance (ANOVA) are widely used statistical methods to compare \ngroup means. For example, the independent sample t-test enables you to compare annual \npersonal income between rural and urban areas and examine the difference in the grade point \naverage (GPA) between male and female students. Using the paired t-test, you can also \ncompare the change in outcomes before and after a treatment is applied. \n \nFor a t-test, the mean of a variable to be compared should be substantively interpretable. \nTechnically, the left-hand side (LHS) variable to be tested should be interval or ratio scaled \n(continuous), whereas the right-hand side (RHS) variable should be binary (categorical). The ttest \ncan also compare the proportions of binary variables. The mean of a binary variable is the \nproportion or percentage of success of the variable. When sample size is large, t-tests and z-test for comparing proportions produce almost the same answer.
Author: Hun Myoung Park
Institution: Indiana University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2151334695