1. Chapter 7Comparing two means So far we have learned how we can analyze observed variables and find relations between them, as in correlation and regression. Regression allows us to draw causal inferences in that we look at how well predictor variables which are supposed to be logically and temporally prior to an outcome variable can predict this outcome variable. However, in regression, we have just measured the predictor variables without having systematic control over them.

2. Manipulating variables Another way to create a causal relation between independent and dependent variable is to systematically manipulate independent (predictor) variables and assess the impact of this manipulation on the dependent (outcome) variable. The advantage of this practice is that you as an experimenter know what you have done since you have deliberately created this manipulation. This gives you control over the independent variables. Since this manipulation is prior to testing its effects (assessing the dependent variable), this fits a causal scenario. For this purpose, a common practice is to compare the means of two groups which have received a different experimental treatment.

3. Two ways of having two means Between groups/subjects, Independent design Each of two independent groups receives a different treatment ? independent t-test Expls: Within groups/subjects, repeated measures Within a single group, two different treatments are administered, in succession ? related t-test Expls:

4. A relevant example (!)Effect of reinforcement on Stats students Group 1: pos reinfo making compliments and rewarding students Group 2: neg. reinfo offending students and making their lives miserable