1. Independent Samples t-Test What is the Purpose?What are the Assumptions?How Does it Work?What is Effect Size?

2. What is the Purpose? Test whether two means are significantly different. Use for a between-subjects design with two groups. Null Hypothesis is that the two groups came from populations with the same mean.

3. Independent observations Interval or ratio level data Normal distribution of dependent variable Homogeneity of variance What are the Assumptions?

4. How Does it Work? Compare the observed difference between means to the Null Hypothesis difference of zero. Where does the observed difference fall in the sampling distribution of the difference between means?

5.  1 -  2 x 1 -x 2 sampling distribution of the difference between means

6. What is Effect Size? Measure of the magnitude of the difference The t-test tells you only whether the result is significant or not. An effect may be large or small whether it is significant or not significant.

7. Effect Size with r 2 Squared point-biserial correlation between the IV and DV Proportion of variance explained in DV by IV Guidelines – Small effect =.01 – Medium effect =.09 – Large effect =.25

8. Effect Size with Cohen’s d Difference between means in units of pooled standard deviation Guidelines – Small effect =.20 – Medium effect =.50 – Large effect =.80