Inferential Statistics Significance Testing Chapter 4

Important Terms Null hypothesis Significance Probability of error (alpha levels) Confidence level Independent t test Dependent t test

Assumptions Group studies – comparing experimental group with control group Representative values to describe performance in both groups – mean and Sd Probability of replication

Comparing Mean Values Mean values will be different Caused by chance or caused by IV

Null Hypothesis Any observable difference between two mean values is simply due to chance Significance testing either accepts or rejects null hypothesis Acceptance means that observable difference was due to chance Rejection means the IV caused the change

Calculation Independent t-test Non independent t-test See pp in supplemental readings

Independent t-test To determine significance between two independent groups, i.e., experimental group and control group Experimental group receives IV; control group does not Was the difference between experimental group mean and control group great enough to state significance?

Significance In essence, what is the likelihood that the group that receives the IV will score higher than the group who does not? In essence, what is the probability that the group who receives the IV will not score higher than the group who does not? In essence, how confident are you that the group who receives the IV will score higher than the group who does not?

Alpha Levels The symbol p means probability of error An alpha level of.05 means probability of error is less than 5 out of 100 times that the IV group might not score higher Or, 95% of the times the IV group will score higher See p. 307 in textbook Appendix C

Alpha levels (cont.) An alpha level of.01 means that less than 1 out of 100 times the IV group might not score higher Or, 99% of the times the IV group will score higher What about an alpha level of.001?

Non independent t-test To determine significance between pre and post tests within one group One group, two treatments Examples