1. Experimental Design Experiment: A type of research study that tests the idea that one variable causes an effect on another variable.

2. Anatomy of an Experiment Example Memory Cues No Memory Cues N 1 = 10 N 2 = 10 M 1 = 16.2 M 2 = 9.9 S 1 = 2.49 S 2 = 2.33 Independent variable = Memory Training Group Dependent variable = Memory for personal history

3. Anatomy of an Experiment Example Experimental Control Group Group Memory Cues No Memory Cues N 1 = 10 N 2 = 10 M 1 = 16.2 M 2 = 9.9 S 1 = 2.49 S 2 = 2.33

4. The study allows the researcher to determine that on variable causes an effect on another variable. Internal Validity

5. Conditions to establish internal validity 1.Time-Order relationship Cause  Effect I.V.  D.V.

6. Conditions to establish internal validity 2.No alternative explanations The difference between the means is due only to the independent variable. Anything else represents a threat to the internal validity of the study

7. Threats to internal validity Non-equivalent control group – Confound: A way in which the groups differ from each other, other than the independent variable. – Controlling for confounds 1. Random assignment to groups 2. Matching

8. Threats to internal validity Floor or Ceiling effects – The independent variable has made the groups different from each other, but the dependent variable is unable to detect it. – Floor effect: The test is so difficult that everyone gets a very low score. – Ceiling effect: The test is so easy that everyone gets a high score. – They make the means closer together than they should be.

9. Threats to internal validity Experimenter effect – The experimenter gives an indication of what they want or expect the subject to do in a particular condition. Participant effect – The participant changes their behavior to fit what they think the researcher is studying.

10. Ways to address experimenter and participant effects – Single-blind study: The participant doesn’t know which condition they’re in. Example: a placebo-controlled condition. – Double-blind design: Neither the participants or the researcher knows which condition the subject is in.

11. The results of the study are generalizable 1.Generalization to different samples – Get the same results if repeat the same study with a different sample (from the same population) – Replication External Validity

12. 2. Generalization to different populations – Get the same results if repeat the same study with a sample from a different population 3.Generalization to different settings – Get the same results under different conditions – The effect is observed in more than one setting – Example: The effect is observed in real life, not just in the laboratory External Validity

13. Independent Samples T-Test Tests the difference between two sample means Memory Cues No Memory Cues N 1 = 10 N 2 = 10 M 1 = 16.2 M 2 = 9.9 S 1 = 2.49 S 2 = 2.33 Prediction of the researcher: The mean of the Memory Cues Group will be significantly higher than the mean of the No Memory Cues Group.

14. Independent Samples T-Test Prediction of the researcher: The mean of the Memory Cues Group will be significantly higher than the mean of the No Memory Cues Group. – Example of a one-tailed test – One-tailed test: One mean is predicted to be higher or lower than the other one. – Two-tailed test: One mean is predicted to be different from the other one.

15. Independent Samples T-Test Prediction of the researcher: The mean of the Memory Cues Group will be significantly higher than the mean of the No Memory Cues Group. – Example of a one-tailed test – Alternative hypothesis: The mean of the Memory Cues Group is significantly higher than the mean of the No Memory Cues Group. – Null hypothesis: The mean of the Memory Cues Group is not significantly higher than the mean of the No Memory Cues Group.

16. Independent Samples T-Test – No way to know for sure which hypothesis is true. – We can know the odds that the null hypothesis is true. – We can decide how unlikely the null hypothesis would have to be before we can’t believe it anymore. That’s the Alpha Level of the test. – “α =.05” means “Reject the null hypothesis if the odds are less than 5% that it’s true”

17. Independent Samples T-Test An independent samples t-test tells you if the odds are less than 5% that the null hypothesis is true. 1. Find the number we’re making our decision about It’s the difference between the two group means M 1 – M 2 = 16.2 – 9.9 = +6.3 We’re comparing this number to a difference of zero. 2. Convert that number to a standard score – In SPSS, t = +5.85 – The difference between the two sample means is 5.85 standard deviations above a difference of zero.

18. Independent Samples T-Test 3. Find how far from zero that number needs to be to be significant  Critical Value for t We predicted that this difference would be in the positive direction, so it’s a one-tailed test. α =.05 Degrees of freedom = N 1 + N 2 – 2  10 + 10 – 2 = 18 Critical value = +1.73 Decision rule: If t ≥ +1.73, reject the null hypothesis.

19. Independent Samples T-Test Conclusion: The mean of the Memory Cues Group is significantly higher than the mean of the No Memory Cues Group, t (18) = 5.85, p <.05.