Page 1 of 8 ID# Exam 3 PS 217, Fall 2008 (You must use your official student ID) As always, the Skidmore Honor Code is in effect. You’ll attest to your adherence to the code at the end of the exam. Read each question carefully and answer it completely, showing all your work (so that you can receive partial credit). The exam is comprised of 7 questions (over 8 pages) totaling 85 points. Have a peaceful and relaxing break. 1. OK, Zubin, this one’s for you (the promised question). In an independent groups ANOVA, the best estimate of population variance (σ2) is MSWithin (MSError). Is that also true for a repeated measures ANOVA? In other words, tell me whether or not MSError in a repeated measures design is a good estimate of population variance, along with your supporting logic. [5 pts]Page 2 of 8 2. Kitamura (2005) was interested in the impact of mood on cognitive processes. Kitamura thought that a positive mood leads to more automatic processing than a negative mood, which leads to more controlled processing. In one study, half of the participants were placed in a positive mood and half in a negative mood (using a mood induction technique). Then they were all given a list of non-famous companies either once or four times. Two days later they were asked to judge the fame of a list of companies, some of which were new (Number = 0) and some that had been seen previously (Number = 1 or 4). Let’s pretend that the participants rated fame on a 7-point Likert-type scale (1 = “not famous” and 7 = “ famous”). Suppose that the data had produced the results seen below. Complete the analysis and interpret the results as completely as you can. [15 pts] 11.522.533.544.5Cell Mean0 1 4CellPositiveNegativeInteraction Line Plot for Mean FameEffect: Number * Mood Tests of Between-Subjects Effects Dependent Variable:Mean Fame Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powerb Mood 39.9 .000 .614 105.055 1.000 Number 38.1 .000 .603 100.337 1.000 Mood * Number 21.0 .000 .456 55.320 1.000 Error 25.1 Corrected Total 124.1Page 3 of 8 3. One area of psychology looks at factors that influence decision-making. One factor that people have studied is how a decision is influenced by the way in which the information is delivered. Even though the information is identical, people’s decisions will differ when the information is placed in a different context (frame). Suppose that a researcher was interested in looking at the impact of four different frames on people’s willingness to engage in risky behavior (or to be more protective). One scenario involves the participant’s willingness to smoke cigarettes. The four frames are: NF = No Frame (so it just asks the participant to imagine that he or she has been smoking for a while and enjoys doing so), AF = Analytical Frame (with statistical information about the scenario, such as how many people die of lung cancer each year), EF = Experiential Frame (which attempts to make the scenario personally relevant by asking the participant to think about a family member dying from lung cancer), and AEF = Analytical + Experiential Frames (which puts the two types of information together). Participants read a series of scenarios and then gave a response that indicated their willingness to engage in risky behavior. The dependent variable is called Protect-Risk, where a positive score indicates a more protective response and a negative score represents a willingness to engage in riskier behavior. Suppose that the researcher is also interested in looking at the impact of age (Young 18-23, Middle 38-43, and Older 58-63). Complete the source table below and interpret the results as completely as you can. [15 pts] Tests of Between-Subjects Effects Dependent Variable:Protect-Risk Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powerb Frame 15.339 57.449 .000 .782 172.346 1.000 Age 33.860 .000 .841 253.634 1.000 Frame * Age .392 .210 .155 8.798 .515 Error Corrected TotalPage 4 of 8 4. Two researchers were interested in studying the effects of reward magnitude on performance. Both researchers used introductory psychology students as participants, the same total number of participants (21), the same type of reward and reward magnitudes ($1, $5, $20), the same apparatus, the same task, and the same performance measure (DV). One researcher used an independent groups design and, on the basis of the results, cannot reject the null hypothesis (that reward has no effect on performance). The other researcher used a repeated measures design and found a statistically significant effect of reward magnitude — larger rewards lead to better performance. Assume that neither study has a major flaw (e.g., repeated measures design is properly counterbalanced, random assignment to conditions). There are two fundamental reasons why the two researchers might have reached different conclusions. One reason concerns the sensitivity of the test of the null hypothesis. The other reason concerns the nature of the participant’s experience in the two studies. Provide me with a clear explanation of the two reasons for the different results that the two researchers obtained. Would you trust the results of one study more than the other? Why? Finally, complete the source tables for the two experimenters seen below. [10 pts] Independent Groups Design (FCrit = 3.55): Source SS df MS F Treatment 28 Error Total 100 Repeated Measures Design (FCrit = 3.23): Source SS df MS F Treatment 20 Within Subject 100 Error (Subj x Treat) Total 200Page 5 of 8 5a. First of all, imagine a repeated measures design with seven levels. Can you tell me why you’d need to counterbalance such a design, what kind of counterbalancing you’d use, and how many participants you’d need? What is the impact of counterbalancing on order and carry-over effects? [3 pts] 5b. OK, now let’s assume that there is a particular order effect—a practice effect. That means that scores on the DV will improve over time as a result of practice. What is the impact on your error term (MSError) of counterbalancing? [2 pts]Page 6 of 8 6. Dr. Ginger Vitas is a health psychologist who is interested in the relationship between dental heath (operationally defined as number of cavities found in an annual checkup)