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CHAPTER 8 EXPERIMENTAL DESIGN.

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Presentation on theme: "CHAPTER 8 EXPERIMENTAL DESIGN."— Presentation transcript:

1 CHAPTER 8 EXPERIMENTAL DESIGN

2 CONFOUNDING AND INTERNAL VALIDITY
Confounding Variable: confounding occurs when the effects of the independent variable and an uncontrolled variable are intertwined so one cannot determine which is responsible for the effect

3 CONFOUNDING AND INTERNAL VALIDITY
Internal Validity: experiment must be designed and conducted so that only the independent variable can be the cause of the results

4 BASIC EXPERIMENTS Posttest-Only Design Must:
Obtain two equivalent groups of participants Selection differences Introduce the independent variable Measure the effect of the independent variable on the dependent variable

5 POSTTEST-ONLY DESIGN

6 BASIC EXPERIMENTS Pretest-Posttest Design
A pretest is given before the experimental manipulation is introduced to make sure groups are equivalent at the beginning of the experiment

7 BASIC EXPERIMENTS Advantages of the pretest-posttest design
Mortality (dropout factor) Assess equivalency of groups with small sample size Can use to select participants for the experiment

8 BASIC EXPERIMENTS Disadvantages of the pretest-posttest design
Time consuming Sensitize participants to what is being studied Demand characteristics Reduces external validity

9

10 ASSIGNING PARTICIPANTS EXPERIMENTAL CONDITIONS
Independent Groups Design Participants participate in only one group Repeated Measures Design Participants Are in All Conditions

11 REPEATED MEASURES DESIGN
Advantages and Disadvantages of Repeated Measures Design Advantages Fewer participants Extremely sensitive to statistical differences Conditions are identical because person is own control group Disadvantages Order effect - Practice effect - Fatigue effect - Contrast effect

12 REPEATED MEASURES DESIGN
Counterbalancing Time Interval Between Treatments

13 COUNTERBALANCING

14 MATCHED PAIRS DESIGN Goal is to Match People on a Participant Characteristic Either the Dependent Measure or a Variable that is Strongly Related to the Dependent Variable Analysis of Covariance


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