Effect size for independent-measures t test - Cohen's d and r squared Tobacco companies have actively attempted to remake their public image by launching a youth smoking prevention advertisement campaign. Melanie Wakefield (a professor of applied psychology and researcher at the Center for Behavioral Research in Cancer in Victoria, Australia) and her colleagues conducted a study to assess the relation between exposure to tobacco companies' youth smoking prevention advertising and youth smoking-related beliefs, intentions, and behaviors. You use Professor Wakefield's research to design an experiment with two groups of middle school students from Ghana. You show the tobacco company's youth smoking prevention ads to one of the groups of students every day for a week at the beginning of their math class. After the week, you assess the groups on the degree to which the students approve/disapprove of adults smoking, using a 5-point Likert scale. You do not have a prediction about the effect of the ads, as they are supposed to prevent smoking, but Professor Wakefield's findings suggested the ads might have the opposite effect if they have any effect at all. There are 225 students in each group. The first group, who saw the ads, scored an average of 3.1 with a sample standard deviation of 1.5 on the 5-point Likert scale. The second group, who did not see the ads, scored an average of 2.8 with a sample standard deviation of 1.6 on the 5-point Likert scale. You find that the estimated standard error of the difference in means is 0.1462, the estimated Cohen's d is, the t statistic is 2.05, and the r^2 is.
Using Cohen's d and Cohen's criteria for evaluating Cohen's d, this is a effect size. Using r^2 and Cohen's criteria for evaluating r^2, this is a effect size.