Experimental Design

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 N1 = 10 N2 = 10 M1 = 16.2 M2 = 9.9 S1 = 2.49 S2 = 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 N1 = 10 N2 = 10 M1 = 16.2 M2 = 9.9 S1 = 2.49 S2 = 2.33

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

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

6. Conditions to establish internal validity • 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. External Validity • The results of the study are generalizable • Generalization to different samples • Get the same results if repeat the same study with a different sample (from the same population) • Replication

12. External Validity 2. Generalization to different populations • Get the same results if repeat the same study with a sample from a different population • 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

13. Independent Samples T-Test • Tests the difference between two sample means Memory Cues No Memory Cues N1 = 10 N2 = 10 M1 = 16.2 M2 = 9.9 S1 = 2.49 S2 = 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. • Find the number we’re making our decision about • It’s the difference between the two group means • M1 – M2 = 16.2 – 9.9 = +6.3 • We’re comparing this number to a difference of zero. • 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 = N1 + N2 – 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.