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- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The management of a technology company is trying to determine the variable that best explains the variation of employee salaries using a sample of 52 full-time employees; see the file P13_08.xlsx. Estimate simple linear regression equations to identify which of the following has the strongest linear relationship with annual salary: the employees gender, age, number of years of relevant work experience prior to employment at the company, number of years of employment at the company, or number of years of post secondary education. Provide support for your conclusion.Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.
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- The following time series represents the number of automobiles sold by a car dealership each of the past five months. t 1 2 3 4 5 Yt 7 12 10 13 14 (a) Construct a time series plot. What type of pattern exists in the data? The time series plot shows a linear trend.The time series plot shows a horizontal pattern. The time series plot shows a seasonal pattern.The time series plot shows a nonlinear trend. (b) Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series. t = (c) What is the forecast for t = 6?In order to monitor the allocation of patrol cars andother police resources, the local police chief, Timothy Kraft, collectsdata on the incidence of crime by city sector. The city isdivided into ten sectors of 1000 residents each. The number ofcrime incidents reported last month in each sector is as follows: Construct a p-chart that plots the rate of crime by sector. Set thecontrol limits to include 99.73 percent of the random variation incrime. ls the crime rate in any sector out of control? Do you haveany suggestions for the reallocation of police resources?The total number of thousands of tons of coal produced per year over a 10-year period for a certain region is provided in the accompanying dataset. Use double exponential smoothing to determine which pairs of values for α and β minimize MAD for this dataset. α=0.2, β=0.8; α=0.4, β=0.2; α=1, β=0.6 First find the MAD for each pair of values, αand β. (Type integers or decimals rounded to two decimal places as needed.) α β MAD 0.2 0.8 enter your response here 0.4 0.2 enter your response here 1 0.6 enter your response here Year Coal Production (thousands of tons) 1 434,327 2 420,424 3 439,047 4 477,190 5 504,186 6 526,951 7 546,821 8 564,887 9 556,706 10 570,980
- 5-21 A college student has just completed her junior year. The following table summarizes her grade-point average (GPA) for each of the past nine quarters: Year Semester GPA Freshman Fall 2.4 Winter 2.9 Spring 3.1 Sophomore Fall 3.2 Winter 3.0 Spring 2.9 Junior Fall 2.8 Winter 3.6 Spring 3.2 Forecast the student’s GPA for the fall semester of her senior year by using a three-period moving average. Forecast the student’s GPA for the fall semester of her senior year by using exponential smoothing with α=0.2 . Which of the two methods provides a more accurate forecast? Justify your answer.Long-Life Insurance has developed a linear model that it uses to determine the amount of term life insurance a family of four should have, based on the current age of the head of the household. The equation is:y = 850 − .1xwherey = Insurance needed ($000)x = Current age of head of household a. Plot the relationship on a graph. b. Use the equation to determine the amount of term life insurance to recommend for a family of four if the head of the household is 30 years old.RDB Company wishes to assign a real estate brokers to one of its 6 sales districts. Based on theprofile of prospective buyers and the past performance of its top 6 brokers, the company estimatesthat average property sales, in lots/month, would be as follows: