Basic Business Statistics, Student Value Edition
14th Edition
ISBN: 9780134685113
Author: Mark L. Berenson, David M. Levine, David F. Stephan, Kathryn Szabat
Publisher: PEARSON
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Chapter 14, Problem 39PS
The chair of the accounting department plans to develop a regression model to predict the grade point average in accounting for those students who are graduating and have completed the accounting major, based on a student’s SAT score and whether the student received a grade of B or higher in the introductory statistics course (
a. Explain the steps involved in developing a regression model for these data. Be sure to indicate the particular models you need to evaluate and compare.
b. Suppose the regression coefficient for the variable whether the student received a grade of B or higher in the introductory statistic course is
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Chapter 14 Solutions
Basic Business Statistics, Student Value Edition
Ch. 14 - For this problem, use the following multiple...Ch. 14 - For this problem, use the following multiple...Ch. 14 - A nonprofit analyst seeks to determine which...Ch. 14 - Profitability remains a challenge for banks and...Ch. 14 - The production of wine is a multibillion-dollar...Ch. 14 - Human resource managers face the business problem...Ch. 14 - Prob. 7PSCh. 14 - Prob. 8PSCh. 14 - The following ANOVA summary table is for a...Ch. 14 - The following ANOVA summary table is for a...
Ch. 14 - A financial analyst engaged in business valuation...Ch. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - In Problem 14.7 on page 542, you used the weekly...Ch. 14 - Prob. 16PSCh. 14 - Prob. 17PSCh. 14 - Prob. 18PSCh. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - Prob. 20PSCh. 14 - Prob. 21PSCh. 14 - Prob. 22PSCh. 14 - Prob. 23PSCh. 14 - Prob. 24PSCh. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem on page 541, you used efficiency ratio...Ch. 14 - Prob. 27PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 29PSCh. 14 - Prob. 30PSCh. 14 - The following is the ANOVA summary table for a...Ch. 14 - The following is the ANOVA summary table for a...Ch. 14 - In Problem 14.5 on page 542, you used alcohol...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - Prob. 35PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 37PSCh. 14 - Suppose X1 is a numerical variable and X2 is a...Ch. 14 - The chair of the accounting department plans to...Ch. 14 - A real estate association in a suburban community...Ch. 14 - In Problem 14.5 on page 542, you developed a...Ch. 14 - In mining engineering, holes are often drilled...Ch. 14 - The owner of a moving company typically has his...Ch. 14 - Prob. 44PSCh. 14 - Zagat’s publishes restaurant rating for various...Ch. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - In Problem 14.5 on page 542, the percentage of...Ch. 14 - Prob. 48PSCh. 14 - The director of a training program for a large...Ch. 14 - Prob. 50PSCh. 14 - Prob. 51PSCh. 14 - Prob. 52PSCh. 14 - Prob. 53PSCh. 14 - Prob. 54PSCh. 14 - Prob. 55PSCh. 14 - Prob. 56PSCh. 14 - Prob. 57PSCh. 14 - An automotive insurance company wants to predict...Ch. 14 - A marketing manager wants to predict customer with...Ch. 14 - A local supermarket manager wants to use two...Ch. 14 - Prob. 61PSCh. 14 - Prob. 62PSCh. 14 - Prob. 63PSCh. 14 - Prob. 64PSCh. 14 - Prob. 65PSCh. 14 - Prob. 66PSCh. 14 - Prob. 67PSCh. 14 - Prob. 68PSCh. 14 - Prob. 69PSCh. 14 - Prob. 70PSCh. 14 - Prob. 71PSCh. 14 - The owner of a moving company typically has his...Ch. 14 - Professional basketball has truly become a sport...Ch. 14 - A sample of 61 house recently listed for sale in...Ch. 14 - Measuring the height of a California redwood tree...Ch. 14 - A sample of 61 houses recently listed for sale in...Ch. 14 - Prob. 77PSCh. 14 - Referring to Problem 14.77, Suppose that an...Ch. 14 - Prob. 79PSCh. 14 - Prob. 80PSCh. 14 - Prob. 81PSCh. 14 - Prob. 82PSCh. 14 - Prob. 83PS
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- Olympic 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_forwardThe following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardFor the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Determine whether the trend appears linear. If so, and assuming the trend continues, find a linear regression model to predict the percent of unemployed in a given year to three decimal places.arrow_forward
- For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city of people 25 years or older who are college graduates is given below, by year. 38. Determine whether the trend appears to be linear.If so, and assuming the trend continues, find alinear regression model to predict the percent of unemployed in a given year to three decimal places.arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forward
- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?arrow_forwardFor the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
- (a) For United States, provide data for the variables below over the years 1993 – 2007: (i) Net migration rate (per 1,000 population) (ii) Total fertility rate (live births per woman) (iii)Unemployment, general level (Thousands) (iv) Wages (v) Life expectancy at birth for both sexes combined (years) Data can be obtained from the UN database http://data.un.org/Explorer.aspx Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided). (iv) Using the 10% level of significance, determine and discuss whether the overall regression equation is statistically significant. In responding, construct and test any appropriate hypothesis. (v) Determine and interpret the confidence interval for the independent variable(s).arrow_forwardCreate the regression equations based on the research model below!arrow_forward(a) For United States, provide data for the variables below over the years 1993 –2007:(i) Net migration rate (per 1,000 population)(ii) Total fertility rate (live births per woman)(iii)Unemployment, general level (Thousands)(iv) Wages(v) Life expectancy at birth for both sexes combined (years)Data can be obtained from the UN database http://data.un.org/Explorer.aspxUsing R-Studio, estimate a regression equation to determine the effect of unemployment,general level, wages and life expectancy at birth for both sexes on the net migration rate.(All codes and regression output should be provided).(i) Write down the regression equation. (ii) Interpret the coefficients and determine which of the individual coefficients in theregression model are statistically significant. In responding, construct and test anyappropriate hypothesis. (iii) Interpret the coefficient of determination.arrow_forward
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