experimental design experiment: a type of research study that tests the idea that one variable...
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Experimental Design
• Experiment: A type of research study that tests the idea that one variable causes an effect on another variable.
Anatomy of an ExperimentExample
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
Anatomy of an ExperimentExample
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
• The study allows the researcher to determine that on variable causes an effect on another variable.
Internal Validity
Conditions to establish internal validity
1. Time-Order relationship
Cause Effect I.V. D.V.
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
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
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.
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.
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.
• 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
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
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.
Independent Samples T-TestPrediction 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.
Independent Samples T-TestPrediction 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.
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”
Independent Samples T-TestAn 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• M1 – M2 = 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.
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.
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.
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