Concept explainers
In Problem 14.6 on page 542, you used full-time voluntary turnover
a. at the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these results,
b. compute the coefficients of partial determination,
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BASIC BUSINESS STATISTICS-STUD.SOLN.MAN
- Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?arrow_forwardTable 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forwardbThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.arrow_forward
- The following information is available regarding the total repair costs of Alexander Design Company for six months of 2022: Using the least-square regression analysis on Excel, construct a cost formula. Run a regression analysis on the data above and provide your response to the following three questions. Round decimals to the nearest tenth (i.e, two decimal points). (1) Provide the regression output and construct a cost model. (2) According to the cost model, what is the estimated total fixed cost? (3) According to the cost model, what is the estimated variable cost per unit?arrow_forwardA 1 Demand 2 WN 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 7.38 8.51 9.52 7.50 9.33 8.28 8.75 7.87 7.10 8.00 7.89 8.15 9.10 8.86 8.90 8.87 9.26 9.00 8.75 7.95 7.65 7.27 8.00 8.50 8.75 9.21 8.27 7.67 7.93 9.26 B PriceDif -0.05 0.25 0.60 0.00 0.25 0.20 0.15 0.05 -0.15 0.15 0.20 0.10 0.40 0.45 0.35 0.30 0.50 0.50 0.40 -0.05 -0.05 -0.10 0.20 0.10 0.50 0.60 -0.05 0.00 0.05 0.55 Carrow_forward1. The following table shows data for the cost of natural gas in Maryland (in dollars per Million Btu) forx years since 1990, values in x column. Define the explanatory and response variables for this problem. b. Use the calculator to obtain the linear regression line of best fit for the original prices; round to three decimal places. a. Write the prediction equation in the form: j = a+ bx Year Price in $ per Million Btu, y 1990 6.28 1991 6.01 1992 2 6.26 1993 3 6.89 1994 4 6.75 1995 5 6.45 1996 6 7.39 1997 7 8.09 1998 8 8.00 1999 9 8.14 10 9.47 11 11.24 12 9.27 2000 2001 2002 In a brief sentenee, interpret the slope in the context of the problem. с. d. Predict the price in dollars per million Btu for the year 2010. Then calculate the residual for the year 2010 if the actual price in 2010 was $11.31 per million Btu. Use formula provided in formula box on page 1. Round to 3 decimals e. What is the correlation coefficient, r, rounded to two decimal places? Is the linear association…arrow_forward
- Midgett Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff suggested that linear regression be employed to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis are as follows: Month MaintenanceCost Machine Hours Jan. $ 5,000 600 Feb. 3,644 440 Mar. 4,400 610 Apr. 3,337 480 May 5,222 660 June 3,390 410 July 3,618 470 Aug. 5,384 630 Sept. 5,114 590 Oct. 4,883 590 Nov. 3,925 430 Dec. 3,850 350 Sum $ 51,767 6,260 Average $ 4,313.92 521.67 Average cost per hour ($51,767/6,260) = $8.27 (rounded to the nearest cent) r = 0.85977 r2 = 0.73920 The percent of the total variance that…arrow_forwardA biologist wants to predict the height of male giraffes, y, in feet, given their age, x1, in years, weight, x2, in pounds, and neck length, x3, in feet. She obtains the multiple regression equation yˆ=7.36+0.00895x1+0.000426x2+0.913x3. Predict the height of a 12-year-old giraffe that weighs 3,100 pounds and has a 7-foot-long neck, rounding to the nearest foot.arrow_forwardJohnson Filtration, Inc. provides maintenance service for water-filtration systems. Suppose that in addition to information on the number of months since the machine was serviced and whether a mechanical or an electrical repair was necessarY, the managers obtained a list showing which repairperson performed the service. The revised data follow. Click on the datafile logo to reference the data. DATA file Repair Time Months Since in Hours Last Service Type of Repair Repairperson 2.9 Electrical Dave Newton 3.0 Mechanical Dave Newton 4.8 8. Electrical Bob Jones 1.8 3 Mechanical Dave Newton 2.9 2 Electrical Dave Newton 4.9 Electrical Bob Jones 4.2 6. Mechanical Bob Jones 4.8 8. Mechanical Bob Jones 4.4 Electrical Bob Jones 4.5 Electrical Dave Newton a. Ignore for now the months since the last maintenance service (1) and the repairperson who performed the service. Develop the estimated simple linear regression equation to predict the repair time (y) given the type of repair (2 ). Recall that…arrow_forward
- The county assessor is studying housing demand and is interested in developing a regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor suspects that the most important variable affecting selling price (measured in thousands of dollars) is the size of house (measured in hundreds of square feet). He randomly selects 15 houses and measures both the selling price and size, as shown in the following table. Complete the table and then use it to determine the estimated regression line. Observation Size Selling Price (x 100 sq. ft.) (x $1,000) ii xixi yiyi xixiyiyi xi2xi2 yi2yi2 1 12 265.2 3,182.40 144.00 70,331.04 2 20.2 279.6 5,647.92 408.04 78,176.16 3 27 311.2 8,402.40 729.00 96,845.44 4 30 328.0 9,840.00 900.00 107,584.00 5 30 352.0 10,560.00 900.00 123,904.00 6 21.4 281.2 6,017.68 457.96 79,073.44 7 21.6 288.4 6,229.44 466.56 83,174.56 8 25.2 292.8 7,378.56 635.04…arrow_forwardThe term 'simple' in simple linear regression refers to the fact that a. the dependent variable is dichotomous b. there are multiple dependent and independent variables c. there is one independent variable d. there is more than one independent variable e. there are no independent variablesarrow_forwardhe management of Lindiwe Accounting Services are concerned about the increase in overtime hours clocked by their senior staff over the past six months of 2022. As the company’s cost accountant, they have assigned you the task of coming up with a reliable way to predict overtime hours and costs for senior staff in the next six months of 2022. You have decided to use linear regression to solve the problem. You have also recorded the following monthly figures for the past six months of 2022. Month Overtime hours Total cost (R) January 478 41 000 February 322 32 000 March 405 37 000 April 308 28 200 May 505 43 500 June 308 29 600 Required: Construct a linear regression equation that your company management can use to predict overtime hours in the future (round all answers to two decimals)arrow_forward
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