Construct the correlation matrix and comment on it. Is the amount of violent crime related to the police officer wage? How about high school graduation?

Use the files to answer complete the assignment as described.

Requirements: Detailed

Page 1 of 2 BA728 HW#3 Business Analytics – BA 728 ONL 01 Fatma Abdel-Raouf Fall I, 2023 Homework Set # 3 Due on September 23, 2023 Answer the following questions. Show all your work. Use Excel to Run the Regressions: 1. Police Pay: The “Police Salary Data” file posted on campus web includes data on the violent crime rates (crimes per 100,000 population) for all 50 states in 2013 along with the high school graduation rate in the state and the average police officer pay. Use this file to answer the following questions: a. Construct the correlation matrix and comment on it. Is the amount of violent crime related to the police officer wage? How about high school graduation? b. Build a model to predict the violent crime rate based on police officer pay and high school graduation rate. Make sure you explain the estimated coefficients. c. What is the value of the F-statistics? What does it mean? d. Are the estimated coefficients significant? Explain. e. How much variation in the violent crime rate is explained by the model? f. Based on your model, what is the predicted violent crime rate in a state with 80% high school graduation rate and average police pay of $30? 2. Health Expenditure: The “Health Expenditure Data” file posted on campus web includes data on the amount of money the country spends on health (as % of its GDP) for different countries in 2004 along with the number of years of schooling and Internet users per 100 people. Use this file to answer the following questions: a. Is the amount of money the country spends on health related to the number of years of education? How about the Internet users (per 100 people)? Explain. b. Build a model to predict the amount of money the country spends on health based on number of years of education and the Internet users (per 100 people). Make sure you explain the estimated coefficients. c. What is the value of the F-statistics? What does it mean? d. Are the estimated coefficients significant? Explain. e. Is this a good model for prediction? Explain.

Page 2 of 2 BA728 HW#3 3. Banking Data: The “banking Data” file posted on campus web has demographic data for different zip codes in the bank’s current market. The data includes average bank account balance, median years of education, median age, median home value, median income, and median household wealth. Use the stepwise regression to build a good model to predict the average bank account balance based on the variables included in the data file. 4. College GPA and SAT Scores: Do you think students’ performance in college is related to their SAT scores? Some believe so. The admission office at a large state university wants to investigate the relationship between students’ GPA in their first year in college and their SAT scores. So, they collected data on students’ first year GPA in college (College GPA), their SAT score (SAT), their high school GPA (HSGPA), and their race (1 for white, 0 otherwise). The data are in the “College GPA Data” file posted on campus web. Use this data file to answer the following questions: a. Build a model to predict students’ college GPA based on their SAT, HS GPA, and race. b. Use the model to predict the first-year college GPA of a white student with a 3.5 HS GPA and SAT scores of 1100, 1300, and 1500. Repeat the same prediction for a non-white student. c. Create two interaction terms: one between SAT and HS GPA and another between SAT and white and use them to extend the model you built in part a to include these interaction terms. d. Use the model you built in part c to recalculate the predictions you made in part b. 5. Predictive Analytics in Business: Find an article in any business publications such as the Wall Street Journal, Financial Times, Business Week, Bloomberg, … that contains any predictive analytics techniques. Read the article and summarize your findings. Make sure you address the following points: – What predictive analytic technique does the article use? – What data are used in the article? What is the result/conclusion of the article? – How can you use the article in decision making?

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