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Question 1 Study A A researcher is interested in Auburn students’ reactions to three plans for a community concert at Toomer’s Corner. Three plans were prepared to be presented to students. The researcher scheduled three 60 minute sessions where he presented one of the three plans and randomly assigned students ONE session to attend. After the presentation, students were asked to complete an evaluation form. Higher scores represent more positive reactions to the concert plan. Enter these data into SPSS ( Attach your results to this exam. Use α = .05 to test the null hypothesis. copying and pasting this table will work, you just need to set the variable names and variable type ) and analyze them using the appropriate statistical procedure. Student Plan Score 1 1 32 2 1 37 3 1 15 4 1 25 5 1 26 6 1 27 7 1 35 8 1 25 9 1 20 10 1 27 11 2 35 12 2 30 13 2 50 14 2 20 15 2 30 16 2 25 17 2 50 18 2 29 19 2 30 20 2 33 21 3 15 22 3 20 23 3 20 24 3 10 25 3 25 26 3 25 27 3 30 28 3 20 29 3 40 30 3 24 Question 1 (continued) Entering and analyzing data (2 points) 1a. Ho: (in words) (1pt.) _________________________________________________________ 1b. H1: (in words) (1pt.) __________________________________________________________ 1c. What type of design was used to collect and analyze the data? (2pts.) __________________________________________________________ 1d. Obtained F = _______________ (1pts.) 1e. Decision about null hypotheses: (1pt.) __________________________________________________________ 1f. What verbal conclusions can be made about the reactions to the three different scenarios? If there is an effect, is it practically significant? Be specific and indicate the source of your conclusions. (4pts.) Question 2 Study B Another researcher was interested the same issue about a concert event. Similar to question 1, this researcher had presentations prepared for each of the three plans. However, this researcher decided to present all three plans to each subject. The three plans were presented, one at a time (in randomized order), to the same group of ten students. Enter these data into SPSS and analyze them using the appropriate statistical procedure (copying ). Attach your output to this exam. Use α = .05 to test the null hypothesis. and pasting this table will work, you just need to set the variable names and variable type A1 A2 A3 Plan1 Plan2 Plan3 S1 25 25 30 S2 20 27 32 S3 24 27 33 S4 40 40 50 S5 30 32 35 S6 30 40 50 S7 20 20 30 S8 25 25 25 Entering and analyzing data (2 points) 2a. Ho: (in words) (1pt.) __________________________________________________________ 2b. H1: (in words) (1pt.) __________________________________________________________ 2c. What type of design was used to analyze the data? (2pts.) __________________________________________________________ 2d. Obtained F = _______________ (1pts.) 2e. Decision about null hypotheses: (1pt.) __________________________________________________________ 2f. What verbal conclusions can be made about the reactions to the three different scenarios? If there is an effect, is it practically significant? Be specific and indicate the source of your conclusions. (4pts.) Question 3 3. Study A in question 1 and study B in question 2 answered the same research question regarding student perceptions. Which design is more appropriate to answer the research question? What is the advantage of that design? Defend your answer with course concepts. (4 pts.) Question 4 A researcher was interested in comparing the way in which three different treatment plans would impact participants’ health status. Participants were randomly assigned to receive one of the three reinforcements and received a comprehensive health screening that included physical and mental indicators. Each group received a health screening before and after the 90 day period to determine the effects of each treatment plan. Higher scores indicate greater health. The three health treatment plans were: 1) 2) 3) Dark Chocolate - This group was instructed to consume a specified amount (although I think some consumed more) of dark chocolate each day. Red Wine – This group was asked to consume 2 glasses of red wine each day. Diet and Exercise – This group was placed on a healthy diet (which did not include red wine or dark chocolate) and a regular exercise program. Results from this study follow. Descriptive Statistics Program Mean Std. Deviation N health_pre dark chocolate 48.7000 10.95496 10 red wine 59.7000 17.14675 10 exercise and health diet 47.7000 16.66700 10 Total 52.0333 15.66125 30 health_post dark chocolate 43.6000 13.10810 10 red wine 78.5000 12.58085 10 exercise and health diet 84.7000 14.32984 10 Total 68.9333 22.46673 30 Multivariate Testsa Effect Value F Hypothesis df Error df Sig. pre_post Pillai's Trace .901 24.132 1.000 27.000 .000 Wilks' Lambda 1.299 24.132 1.000 27.000 .000 Hotelling's Trace .801 24.132 1.000 27.000 .000 Roy's Largest Root .751 24.132 1.000 27.000 .000 pre_post * program Pillai's Trace 1.103 23.368 2.000 27.000 .000 Wilks' Lambda 1.097 23.368 2.000 27.000 .000 Hotelling's Trace .703 23.368 2.000 27.000 .000 Roy's Largest Root .123 23.368 2.000 27.000 .000 Mauchly's Test of Sphericitya Measure: MEASURE_1 Within Subjects Effect Mauchly's W Approx. Chi- Square df Sig. Epsilonb Greenhouse- Geisser Huynh-Feldt Lower-bound pre_post .937 .904 2 .637 .941 1.000 .500 Tests of Within-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. pre_post 4284.150 1 4284.150 24.132 .000 pre_post * program 8297.100 2 4148.550 23.368 .000 Error(pre_post) 4793.250 27 177.528 Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Intercept Program Error 219494.017 2408.433 6252.050 1 2 27 219494.017 1204.217 231.557 947.903 5.201 .000 .012 4a. What type of design was used to analyze these data? (2 pt) 4b. Complete the following table of findings after examining the results. Note that the number of rows below does NOT indicate the appropriate number of effects (there may be fewer). (3 pts) Variable/Effect Is effect between, repeated, or mixed? Obtained Result (F value) Decision about null hypothesis 4c. Graph the interaction below (you may use Excel or hand draw): (2 pts) 4d. Imagine you have all the follow-up and posthoc results you need. State what additional tests are needed. Based on the results reported above in 4b and your graphed interaction in 4c, what verbal conclusions can be made? Be specific about which test(s) will yield each conclusion. (5 pts) Question 5 A researcher was interested in whether customer service agents received higher customer satisfaction ratings when they used different modes of communication (variable=mode of service) or when they received a new training program (variable=training).From a sample of agents, the researcher was able to examine the following data. Examine the SPSS output carefully and answer the questions that follow. Descriptive Statistics Dependent Variable: Customer Satisfaction Scale Mode of service Training Mean Std. Deviation N Face-to-face No 31.25 5.242 12 yes 35.89 6.471 160 Total 35.57 6.489 172 Phone Messaging Total no yes Total no yes Total no 27.53 34.36 33.34 24.29 34.45 33.18 27.31 6.177 6.097 6.558 6.752 6.829 7.586 6.621 19 108 127 17 119 136 48 yes 35.02 6.507 387 Total 34.17 6.947 435 Tests of Between-Subjects Effects Dependent Variable: Customer Satisfaction Scale Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model Intercept Mode Training Mode * Training Error Total Corrected Total 3087.946a 161229.127 451.635 2140.877 203.217 17856.122 528917.000 20944.069 5 1 617.589 161229.127 225.818 2140.877 101.609 41.623 14.838 3873.590 5.425 51.435 2.441 .000 .000 .005 .000 .088 .147 .900 .025 .107 .011 2 1 2 429 435 434 a. R Squared = .147 (Adjusted R Squared = .138) Multiple Comparisons Dependent Variable: Customer Satisfaction Scale LSD (I) Mode of service (J) Mode of service Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Face-to-face Messaging Phone Messaging 2.23* .755 .003 .75 3.71 Phone Face-to-face Phone Face-to-face 2.39* -2.23* .15 -2.39* .740 .755 .796 .740 .001 .003 .846 .001 .93 -3.71 -1.41 -3.84 3.84 -.75 1.72 -.93 Messaging -.15 .796 .846 -1.72 1.41 Based on observed means. The error term is Mean Square(Error) = 41.623. *. The mean difference is significant at the .05 level. Question 5 (continued) 5a. What type of ANOVA design was used to analyze these data? (2 pt.) 5b. Report the findings from each hypothesis in this design. Note that the number of rows below does NOT indicate the appropriate number of effects (there may be fewer). (3 pts) Variable/Effect Is effect between, repeated, or mixed? Obtained Result (F value) Decision about null hypothesis 5c. What can be concluded regarding the influence of experience and recommendations on customer service ratings? If there are effects, are they practically significant? Be specific and indicate the source of your conclusions. (5 pts.)

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Question 1
Entering and analyzing data
1a. Ho: (in words)
There is no significant difference between scores in terms of plan type. In other words, scores do not change by plan type. Scores are equal for each of plan.
1b. H1: (in words)
There is a significant difference between scores by plan type. At least one group is different from the others. In other words, scores differ by groups (in here “plan”).
1c. What type of design was used to collect and analyze the data?
Simple analysis of variance (One Way ANOVA)
1d. Obtained F = 3.924 with 0.032 p-value.
1e. Decision about null hypotheses:
F critical value for df: (2,27) at 0.05 alpha is equal to 3.35. F obtained is greater than F critical. Therefore, we can reject the null. (Also, p-value is 0.032 less than 0.05 that means rejections of the null.)
1f. What verbal conclusions can be made about the reactions to the three different scenarios? If there is an effect, is it practically significant? Be specific and indicate the source of your conclusions.
Since the null hypothesis is rejected, there is a significant effect of plan types. According to descriptive statistics, the average scores by plans are 26.9, 33.2 and 22.9 respectively. As we can see, mean scores are different and these findings are significant at 0.05 level. This indicates that at least two groups (plan1-plan2 or plan1-plan3 or plan2-plan3) are different from each other. In order to see which groups are significantly different, I conducted Tukey Test and found that only scores of Plan 2 and Plan 3 are significantly different (p-value is equal to 0.026 and significant at 0.05 level). All SPSS tables are given in Attachment-1.

Entering and analyzing data
2a. Ho: (in words)
There is no overall significant difference between the means of scores at the different plans. Scores do not differ by plan. Plan type has no effect on the scores. There is no significant change in scores at plan 1, plan 2 and plan 3.
2b. H1: (in words)
There is an overall significant difference between the means of scores at the different plans. Score are not equal. Plan type has a significant effect on the scores.
2c. What type of design was used to analyze the data?
Repeated measures analysis of variance (One-way).
2d. Obtained F = 9.843 (Wilks’ Lambda – Multivariate Test...

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