1.A policy analyst is attempting to determine which mechanisms are most effective in resolving problems brought by citizens to local government. The analyst has broken down the mechanisms into two categories, normal bureaucratic channels and through an ombudsman, and divided problem resolution into two categories: yes (resolved) and no (not resolved), according to the citizen. A random sample of 300 citizens who have approached the bureaucracy with a problem shows that 67 of those who went through normal bureaucratic channels felt that their problem had been resolved, while 147 who used normal channels felt that their problem had not been resolved. Of the citizens who brought their problem to an ombudsman, 26 felt that their problem had been resolved and 60 felt that their problem had not been resolved. Construct a contingency table from these data and analyze the results. Does the sample of citizens feel that the problems are being resolved? Which mechanism is more effective at resolving problems? Support your answer.

2. A professor of Education is interested in the relationship between students’ visits to office hours held by professors and their final grades in the course. She has obtained sample data from Hardk nocks University regarding these two variables. These data are cross-tabulated below.

She hypothesizes that the more visits made by a student to office hours, the higher the likely grade. Calculate the chi-square statistics for this table. Are the two variables related in all students? Explain your answer.

3. Rita Sharp, Director of Operations at the Farnsworth Museum of Industrial Arts, has gathered weekly visitor data for the past year. Rita is interested in explaining why the number of visitors (NUMV) varies from week to week. Rita has data on two independent variables. The first is a dummy variable coded 1 for weeks when new items went on display and coded 0 for all other weeks (NITEM). The second is a variable for the price of an admissions ticket because part of the museum’s marketing strategy is to have weekly reduced-price admission promotions (TPRICE). The director asks you to generate a regression equation using these data. Use the data in the Excel spreadsheet to (1) produce a regression model, (2) interpret the parameters, and (3) access the goodness of fit of the model. In summarizing the findings, what should you tell the director?

4. Dr. Susan Marsh, a physician at the Health Living Community Center, would like to obtain a better understanding of the factors that contribute to obesity in the community. Engaging research has suggested that proximity to convenience stores may be a contributing factor to obesity. To test this argument, she asks one of her assistants to collect data for a sample of 50 randomly selected male clients. The first variable collected is the distance of each clients’ home to the nearest convenience store (in miles, DISTANCE), and the second variable for the analysis if client weight (WEIGHT). Use the data in the Excel spreadsheet to (1) draw a scatter plot, (2) calculate the correlation coefficient between the two variables, and (3) interpret the coefficient. Based on these findings, can you conclude that proximity to convenience stores leads to obesity?

5. Darcie Warner, an analyst at the U.S. Census Bureau, is researching why the percentage of households without access to the internet varies by state. This measure (NOINT) will be the dependent variable in her empirical analysis. She has collected data on what she believes are two relevant explanatory variables: the percentage of foreign-born residents by state (PFORB) and the poverty rate by state (POVERTY). These are her independent variables. Ms. Warner hypothesizes that states with higher percentages of foreign-born residents are more urban and cosmopolitan; therefore, she expects this variable to be negatively related to the dependent variable. In the case of poverty, Ms. Warner expects to see a positive relationship between poverty rates and lack of household internet access. Upon generating a regression equation with the data in the Excel spreadsheet, what can Ms. Warner say about her hypotheses?

Answer rating: 100% (QA)

1 i Contingency table constriction Problem Solutions Mechanism Resolved Not Resolved Total Normal Bureaucracy 67 147 214 Ombudsman 26 60 86 Total 93 207 300 ii Does the sample of citizens feel that th... View the full answer