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Provide your answers below to each question. Do not delete the questions. Please do not use red font. Blue or green is OK. Part I (35 POINTS) The General Social Survey research department was tasked to determine the number of hours per day government employees in the USA spent on emailing. The department reported the data for a sample of 1765 government employees from GSS 2018 data on age (number of years), sex of respondent (1=males, 2=females), total family income (in constant dollars), and hours worked last week. Refer to the SPSS output below. Conduct the full regression analysis. Regression Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .312a .097 .092 12.165 a. Predictors: (Constant), Respondents sex, Age of respondent, Number of hours worked last week, Respondent income in constant dollars ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 9764.913 4 2441.228 16.495 .000b Residual 90424.483 611 147.994 Total 100189.396 615 a. Dependent Variable: Email hours per week b. Predictors: (Constant), Respondents sex, Age of respondent, Number of hours worked last week, Respondent income in constant dollars Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -2.633 3.044 -.865 .387 Age of respondent -.017 .036 -.019 -.483 .629 Number of hours worked last week .090 .036 .102 2.464 .014 Respondent income in constant dollars 8.863E-5 .000 .278 6.659 .000 Respondents sex 3.523 1.025 .138 3.438 .001 a. Dependent Variable: Email hours per week Hint: For the coefficient that ends in E-5, move the point 5 decimal places to the left 1. Which variables are independent variables? 2. Which variable is the dependent variable? 3. What does coefficient of determination (R2) tell you? 4. What is the intercept value? What can it indicate here? 5. Is the model overall significant? 6. Determine the multiple regression equation: 7. Discuss significant regression coefficients 8. What variable has the strongest effect on the number of hours US government employees spent emailing? 9. What is the estimated number of hours emailing per day for a woman who works 40 hours per week and who earns $50.000 per year? Part II (35 POINTS) Give the full logistic regression analysis of the SPSS 2014 output provided below. The coding for the dependent variable is presented in the SPSS output. Interpret and include in your regression equation only significant coefficients (use alpha= 0.05). The question that the respondents were asked is: “Would you favor or oppose the teaching of sex education in public schools?” (Favor= 1; Oppose=0) Coding for variables: polviews: 1. Extremely liberal 2. Liberal 3. Slightly Liberal 4. Moderate 5. Slightly Conservative 6. Conservative 7. Extremely Conservative pillok: Birth Control to Teenagers 14-16 Question asked: Do you strongly agree, agree, disagree, or strongly disagree that it is acceptable to make birth control devices available to teenagers, age 14-16? 1. Strongly Agree 2. Agree 3. Disagree 4. Strongly disagree educ: Highest year of school completed Logistic Regression Case Processing Summary Unweighted Casesa N Percent Selected Cases Included in Analysis 1579 62.2 Missing Cases 959 37.8 Total 2538 100.0 Unselected Cases 0 .0 Total 2538 100.0 a. If weight is in effect, see classification table for the total number of cases. Dependent Variable Encoding Original Value Internal Value Oppose 0 Favor 1 Categorical Variables Codings Frequency Parameter coding (1) (2) (3) BIRTH CONTROL TO TEENAGERS 14-16 STRONGLY AGREE 403 1.000 .000 .000 AGREE 518 .000 1.000 .000 DISAGREE 389 .000 .000 1.000 STRONGLY DISAGREE 269 .000 .000 .000 Block 0: Beginning Block Classification Tablea,b Observed Predicted SEX EDUCATION IN PUBLIC SCHOOLS RECODED Percentage Correct Oppose Favor Step 0 SEX EDUCATION IN PUBLIC SCHOOLS RECODED Oppose 0 141 .0 Favor 0 1438 100.0 Overall Percentage 91.1 a. Constant is included in the model. b. The cut value is .500 Block 1: Method = Enter Omnibus Tests of Model Coefficients Chi-square df Sig. Step 1 Step 161.537 6 .000 Block 161.537 6 .000 Model 161.537 6 .000 Model Summary Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square 1 788.732a .097 .215 a. Estimation terminated at iteration number 7 because parameter estimates changed by less than .001. Classification Tablea Observed Predicted SEX EDUCATION IN PUBLIC SCHOOLS RECODED Percentage Correct Oppose Favor Step 1 SEX EDUCATION IN PUBLIC SCHOOLS RECODED Oppose 7 134 5.0 Favor 9 1429 99.4 Overall Percentage 90.9 a. The cut value is .500 Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 1a AGE OF RESPONDENT -.020 .006 13.774 1 .000 .980 HIGHEST YEAR OF SCHOOL COMPLETED .100 .031 10.271 1 .001 1.105 THINK OF SELF AS LIBERAL OR CONSERVATIVE -.447 .074 36.855 1 .000 .639 BIRTH CONTROL TO TEENAGERS 14-16 45.412 3 .000 BIRTH CONTROL TO TEENAGERS 14-16(1) 1.940 .364 28.347 1 .000 6.957 BIRTH CONTROL TO TEENAGERS 14-16(2) 1.402 .261 28.755 1 .000 4.064 BIRTH CONTROL TO TEENAGERS 14-16(3) .800 .227 12.437 1 .000 2.226 Constant 3.177 .646 24.168 1 .000 23.966 a. Variable(s) entered on step 1: AGE OF RESPONDENT, HIGHEST YEAR OF SCHOOL COMPLETED, THINK OF SELF AS LIBERAL OR CONSERVATIVE, BIRTH CONTROL TO TEENAGERS 14-16. 1. What variables are independent variables? 2. What variable is the dependent variable? 3. Determine the logistic regression equation 4. Determine which independent variables are statistically significant and interpret the regression (B) coefficients Variable Name Level of significance 5. Interpret the Exp (B) coefficients Variable Name Level of significance 6. Provide overall conclusion Part III (30 POINTS) Review the article: Anna Ya Ni and Stuart Bretschneider. “The Decision to Contract Out: A study of Contracting for E-Government Services in State Governments.” Public Administration Review 64, 3:531-544. It is available on Module 9 in the Readings folder. Write you review keeping the following questions in mind: 1. What is the policy analysis question? 2. What is the unit of analysis (identify a case in this study)? 3. What method of analysis is used in this research? 4. Draw the model using boxes and arrows diagram. 5. Indicate the dependent and independent variables used in this model with their level of measurement and unit of measurement; fill in the table provided below. You can add or delete rows from the table. Unit of Analysis: Variable Name Level of Measurement Unit of measurement/coding Independent/Dependent Variable 6. Explain the logistic regression results. Use the table format and the information you have inputted in question 5. Hypothesis Give a number to hypothesis. (H1 etc.) It is conventional way to indicate hypotheses. Logistic Regression results 7. How type of service influences the outsourcing decision? Extra credit (10 points) Using your regression equation from part II, calculate the probability of favoring teaching of sex education in public schools for a 40-year-old person with some college education (15 years), liberal in political views. That person strongly agrees that birth control pills should be available to teenagers. 6 Th e Decision to Contract Out: A Study of Contracting for E-Government Services in State Governments The Decision to Contract Out 531 Government contracting, especially for information technology products and services, has accelerated in recent years in the United States. Drawing on the insights of privatization studies, the authors examine the economic and political rationales underpinning government decisions to contract out e-government services. Th is article tests the extent to which economic and political rationality infl uence governments’ contracting decisions using data from multiple sources: a survey conducted by National Association of State Chief Information Offi cers, a survey by the National Association of State Procure- ment Offi cers, the Council of State Legislatures, and macro-level state data from the U.S. Census Bureau. Important factors aff ecting the state-level contracting decision are population size, market size, the competitive- ness of the bidding process, the professional management of contracts, the partisan composition of legislatures, and political competition. Political rationales appear to play a major role in state contracting decisions. Some arguments associated with markets and economic rationality are clearly politically motivated. During the last two decades, as privatization has gained political currency, contracts with private sector organizations have increased dramatically in bipartisan governments. Privatization advocates believe that contracting out is an eff ective tool for government to reduce costs, increase effi - ciency, improve services, and encourage innovations ( Gore 1993; Kettl 1993; Osborne and Gaebler 1992; Salamon 1989; Savas 1987 ). Along with the growth of contracting out, interest in electronic government (e-government) has also grown for many of the same reasons. A substantial number of e-government initiatives have made heavy use of contracting out ( Gant, Gant, and Johnson 2002 ). Th e popularity of contracting out services such as data processing, Web site hosting, training, and project management has spread across all levels of government. It is believed that contracting helps governments over- come fi nancial diffi culties in accessing the esoteric expertise and professional management skills of private fi rms to develop e-government applications ( Brown and Brudney 1998; Chen and Perry 2002 ). Growing interest in privatization has fueled many