Essentials of Business Analytics (MindTap Course List)
2nd Edition
ISBN: 9781305627734
Author: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson
Publisher: Cengage Learning
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Textbook Question
Chapter 8, Problem 19P
Because of high tuition costs at state and private universities, enrollments at community colleges have increased dramatically in recent years. The following data show the enrollment for Jefferson Community College for the nine most recent years:
- a. Construct a time series plot. What type of pattern exists in the data?
- b. Use simple linear
regression analysis to find the parameters for the line that minimizes MSE for this time series. - c. What is the forecast for year 10?
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The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below.
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The Seneca Children’s Fund (SCC) is a local charity that runs a summer camp for disadvantagedchildren. The fund’s board of directors has been working very hard over recentyears to decrease the amount of overhead expenses, a major factor in how charities arerated by independent agencies. The following data show the percentage of the money SCChas raised that was spent on administrative and fund-raising expenses over the last sevenyears.
a. Construct a time series plot. What type of pattern exists in the data?b. Use simple linear regression analysis to find the parameters for the line that minimizesMSE for this time series.c. Forecast the percentage of administrative expenses for year 8.d. If SCC can maintain its current trend in reducing administrative expenses, how longwill it take SCC to achieve a level of 5 percent or less?
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Chapter 8 Solutions
Essentials of Business Analytics (MindTap Course List)
Ch. 8 - Consider the following time series data:
Using...Ch. 8 - Refer to the time series data in Problem 1. Using...Ch. 8 - Problems 1 and 2 used different forecasting...Ch. 8 - Consider the following time series data:
Compute...Ch. 8 - Consider the following time series...Ch. 8 - Consider the following time series...Ch. 8 - Refer to the gasoline sales time series data in...Ch. 8 - Prob. 8PCh. 8 - Prob. 9PCh. 8 - Prob. 10P
Ch. 8 - For the Hawkins Company, the monthly percentages...Ch. 8 - Corporate triple A bond interest rates for 12...Ch. 8 - The values of Alabama building contracts (in...Ch. 8 - The following time series shows the sales of a...Ch. 8 - Prob. 15PCh. 8 - The following table reports the percentage of...Ch. 8 - Consider the following time series: a. Construct a...Ch. 8 - Consider the following time series:
Construct a...Ch. 8 - Because of high tuition costs at state and private...Ch. 8 - The Seneca Children’s Fund (SCF) is a local...Ch. 8 - The president of a small manufacturing firm is...Ch. 8 - Consider the following time series: a. Construct a...Ch. 8 - Consider the following time series...Ch. 8 - The quarterly sales data (number of copies sold)...Ch. 8 - Prob. 25PCh. 8 - South Shore Construction builds permanent docks...Ch. 8 - Hogs & Dawgs is an ice cream parlor on the border...Ch. 8 - Donna Nickles manages a gasoline station on the...Ch. 8 - The Vintage Restaurant, on Captiva Island near...
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
- One of the biggest changes in higher education in recent years has been the growth of online universities. The Online Education Database is an independent organization whose mission is to build a comprehensive list of the top accredited online colleges. The following table shows the retention rate (%) and the graduation rate (%) for 29 online colleges.a). Use Excel Data Analysis Tool – Regression to get the relationship between the two variables;b). Create a scatter diagram for the two variables and display regression equation and R square on chart, then explain the relationship between the variables;c). Did the estimated regression equation provide a good fit?d). Suppose you were the president of South University. After reviewing the results, would you be able to use the regression result for forecasting. College RR(%) GR(%) Western International University 7 25 South University 51 25 University of Phoenix 4 28 American InterContinental University 29 32 Franklin…arrow_forwardIn retail, a store manager uses time series models to understand shopping trends. Review the scatter plot of the store’s sales from 2010 through 2021 to answer the questions. See attached as image. Here is the data for Fiscal Year and Sales: Fiscal Year Sales 2010 $260,123.00 2011 $256,853.00 2012 $274,366.00 2013 $290,525.00 2014 $322,318.00 2015 $380,921.00 2016 $541,925.00 2017 $909,050.00 2018 $1,817,521.00 2019 $3,206,564.00 2020 $4,921,005.00 2021 $5,686,338.00 Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components? The model can be additive or multiplicative. When do you use each? Review the scatter plot of the exponential trend of the time series data. Do you observe a trend? If so, what type of trend do you observe? What predictions might you make about the store’s annual sales over the next few years?arrow_forwardThe points on the population regression line will have coordinates Group of answer choices (tip, average sale amount). (tip, predicted sale amount) (predicted sale amount, tip). (tip, sale amount). (average sale amount, tip). (predicted tip, sale amount). (sale amount, predicted tip). (sale amount, tip). (sale amount, average tip). (average tip, sale amount).arrow_forward
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