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BPS - 3rd Ed. Chapter 81 Producing Data: Experiments.

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Presentation on theme: "BPS - 3rd Ed. Chapter 81 Producing Data: Experiments."— Presentation transcript:

1 BPS - 3rd Ed. Chapter 81 Producing Data: Experiments

2 BPS - 3rd Ed. Chapter 82 Explanatory and Response Variables u Response variable measures what happens to the individuals in the study u In an experiment, the investigator controls the values of the explanatory variable in individuals to see if he or she can influences the response variable

3 BPS - 3rd Ed. Chapter 83 Experiments: Vocabulary u Subjects = people studied in an experiment u Factors = explanatory variables (specific experimental condition applied to subjects) u Treatment = a combination of a specific set of factors

4 BPS - 3rd Ed. Chapter 84 Case Study Effects of TV Advertising p. 200 in text

5 BPS - 3rd Ed. Chapter 85 Case Study Objective: To determine the effects of length of message and how often message is repeated Effects of TV Advertising

6 BPS - 3rd Ed. Chapter 86 Case Study u Subjects: a sample of undergraduate students u Subjects viewed a 40-minute television program that included ads for a digital camera

7 BPS - 3rd Ed. Chapter 87 Case Study u Factors –Some subjects saw a 30-second commercial; others saw a 90-second version –Commercial were shown either 1, 3, or 5 times during the program u Thus: two factors: –length of the commercial (2 levels) –number of repetitions (3 levels)

8 BPS - 3rd Ed. Chapter 88 Case Study u The 6 combinations of factors, i.e., 6 treatments Factor B: Repetitions 1 time3 times5 times Factor A: Length 30 seconds 123 90 seconds 456 Subjects assigned to Treatment 3 see a 30-second ad five times during the program

9 BPS - 3rd Ed. Chapter 89 Case Study u After viewing, subjects answered questions about –recall of the ad –their attitude toward the camera –their intention to purchase u Three response variables

10 BPS - 3rd Ed. Chapter 810 Comparative Experiments u Comparison is the leading principle –Effects of treatment can be judged only in relation to what happens in a similar group –This sorts out changes that are unrelated to treatment u You cannot assess the effect of a treatment in isolation because: –Many factors contribute to a response –Conditions change on their own –People are open to suggestion (Placebo effect) –Observations changes things (Hawthorne effect)

11 BPS - 3rd Ed. Chapter 811 Randomized Experiments u Randomization is the second leading principle u Randomization = use impersonal chance mechanisms to assign treatments u Randomization balances lurking variables across treatments groups

12 BPS - 3rd Ed. Chapter 812 Example: Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600) u Subjects: 60 people u Explanatory variable: Treatment assignment –Nicotine patch –Control (placebo) patch Random assignment of treatment! u Response variable: Cessation of smoking (yes/no)

13 BPS - 3rd Ed. Chapter 813 Outline of Experiment Random Assignment Group 1 30 smokers Treatment 1 Nicotine Patch Compare Cessation rates Group 2 30 smokers Treatment 2 Placebo Patch

14 BPS - 3rd Ed. Chapter 814 Randomizing the Treatment  Assign labels 01,…,60 to subjects u Use random digits (TABLE B) –Select line at random (say 102) 73|67|64|71|50|99|40|0 0|19|27 –First four subjects are 50, 40, 19, and 27 –Keep using table until you get 30 subjects in Group 1 –Remaining subjects are assigned to Group 2

15 BPS - 3rd Ed. Chapter 815 Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) u Subjects (30 undergraduate students) u Variables: –Explanatory: 3 treatments (see below) –Response: Change in Stanford-Binet IQ score u Treatment: u Group 1: Listen to Mozart u Group 2: Listen to relaxation tapes u Group 3: Silence u Random assignment of treatments

16 BPS - 3rd Ed. Chapter 816 Outline of Experiment Random Assignment Group 1 10 students Treatment 1 Mozart Compare Change in IQ score Group 3 10 students Treatment 3 Silence Group 2 10 students Treatment 2 Relaxation

17 BPS - 3rd Ed. Chapter 817 Logic of Randomized Comparative Experiments u Random assignment ensure  difference in response due to either –Treatment –Chance in the assignment of treatments u If an experiment finds a difference among groups, we ask whether this difference is (“real”) or due to the chance assignment u If the observed difference is larger than what would be expected just by chance, then it is statistically significant

18 BPS - 3rd Ed. Chapter 818 Illustrative example u Consider an experiment of weight gain in laboratory rats u There would be differences in weight gain even if both groups received the same diet –Just by luck, some faster-growing rats would end in one group or the other u If we assign many rats to each group, the effects of chance will balance out u Key concept: use enough controls to balance out chance differences


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