SPSS Week 5 Imagine a researcher is interested in the relationships among teachers' self-esteem and productivity. A randomly selected sample of 40 teachers completed a questionnaire including a number of demographic questions as well as measures to assess their self-esteem and productivity. Below are the demographic data and participants' responses for the self-esteem measure (100-point scale) and the productivity measure (50-point scale). Use these data to answer the questions below (these data have already been entered in a SPSS file; see the note below the data table). Gender (M = male, F = female) M M F M F F F F M M F F F F M M F M F M M M F F M F M M F M F Self-esteem scores (ScoreOne) 64 68 74 75 76 79 80 82 68 70 74 76 78 79 82 85 71 73 75 77 78 80 83 86 73 74 77 77 78 81 84 Productivity Scores (ProdOne) 25 28 36 38 34 36 40 41 22 38 39 34 38 37 45 46 30 34 33 36 38 42 46 49 37 38 32 35 36 45 49 F F M F F M M F F 87 77 71 75 76 79 83 89 91 48 36 33 34 36 38 48 48 49 Download the SPSS data set: teachersurvey.sav. Not all of the variables in that SPSS file will be used for this assignment. In this SPSS assignment, use the tools learned in this course thus far, with an emphasis on the tools acquired in Gravetter and Wallnau (2013) Chapters 7 and 8, to respond to questions related to sampling and hypothesis testing. 1.) Imagine the researcher is now interested in the productivity of all five (5) foreign language teachers in one school. The population has the following productivity scores (participant #, productivity score): #16, 46; #26, 38; #33, 36; #38, 48; and #40, 49. Use this population as the basis for constructing a frequency distribution histogram of sample means for n = 2. Parts a and b of this item will be done manually and the responses will be entered into a Word File in APA format. a) How many unique samples of size 2 can be obtained from the population of productivity scores of all 5 foreign language teachers? (Hint: 46, 38 is the same as 38, 46...order is not important). b. Of those possible samples of 2, how many would result in a mean score of equal to or less than 42? Calculate a mean for each of the samples of size 2. Report those means in a table. c. Use SPSS to calculate the mean, standard deviation, and standard error for all of the productivity scores. Review Activities 2, 3, and 4 if it is unclear how to compute those values. How does the population mean relate to the sample means calculated in parts a and b? 2.) Compute the mean, standard deviation, and standard of error of productive for teachers in each topic area (subject taught). (Hint: Use ANALYZE=>DESCRIPTIVE STATISTICS=>EXPLORE). Use APA format to report the results (APA, Chapter 5). 3.) If there were 100 (rather than 40) teachers providing data for each topic area, how would the standard error of the mean change? Why? The mean? Why? The standard deviation? Why? 4.) Imagine a program to improve productivity was implemented. Write an appropriate research question to learn if the program is effective. Aligned with this research question, write a null and an alternative hypothesis. Each hypothesis should be written in words as well as with the use of symbols (Ho:, Ha). 5.) Now, assume an assessment of the impact of the program on teachers' productivity was needed. Suppose the average score among all teachers on the productivity measure was = 36. In the current randomly selected sample of 40 teachers, the average productivity score was 38.18. However, before a test to determine whether the program had a significant effect, there are a number of factors in need of consideration: a.) Select an appropriate alpha level. Explain this research decision (i.e., why specific value was selected) and its meaning. b.) What assumptions must be met for this test? c.) What are the two different types of errors made during a hypothesis test? How can the likelihood of each error occurring be minimized? d.) Once the statistical test has been conducted, under what conditions would the null hypothesis be rejected? How would it be determined if the null hypothesis should be rejected? e.) After conducting statistical tests, it is common practice to compute an effect size. Why is this value important