Applied Statistics in Business and Economics
5th Edition
ISBN: 9780077837303
Author: David Doane, Lori Seward Senior Instructor of Operations Management
Publisher: McGraw-Hill Education
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Chapter 12, Problem 9CR
a.
To determine
Explainwhat is residual.
b.
To determine
Explain standardized residual and its uses.
c.
To determine
Explain two alternative ways to identify unusual residuals.
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Chapter 12 Solutions
Applied Statistics in Business and Economics
Ch. 12.1 - Prob. 1SECh. 12.1 - Prob. 2SECh. 12.1 - Prob. 3SECh. 12.1 - Prob. 4SECh. 12.1 - Prob. 5SECh. 12.1 - Prob. 6SECh. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - Prob. 9SECh. 12.2 - (a) Interpret the slope of the fitted regression...
Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.3 - Prob. 12SECh. 12.3 - Prob. 13SECh. 12.3 - The regression equation Credits = 15.4 .07 Work...Ch. 12.3 - Below are fitted regressions for Y = asking price...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - Prob. 24SECh. 12.5 - A regression was performed using data on 32 NFL...Ch. 12.5 - A regression was performed using data on 16...Ch. 12.6 - Prob. 27SECh. 12.6 - Prob. 28SECh. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.7 - Refer to the Weekly Earnings data set below. (a)...Ch. 12.7 - Prob. 33SECh. 12.8 - Prob. 34SECh. 12.8 - Prob. 35SECh. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - Prob. 38SECh. 12.9 - Prob. 39SECh. 12 - (a) How does correlation analysis differ from...Ch. 12 - (a) What is a simple regression model? (b) State...Ch. 12 - (a) Explain how you fit a regression to an Excel...Ch. 12 - (a) Explain the logic of the ordinary least...Ch. 12 - (a) Why cant we use the sum of the residuals to...Ch. 12 - Prob. 6CRCh. 12 - Prob. 7CRCh. 12 - Prob. 8CRCh. 12 - Prob. 9CRCh. 12 - Prob. 10CRCh. 12 - Prob. 11CRCh. 12 - Prob. 12CRCh. 12 - (a) What is heteroscedasticity? Identify its two...Ch. 12 - (a) What is autocorrelation? Identify two main...Ch. 12 - Prob. 15CRCh. 12 - Prob. 16CRCh. 12 - (a) What is a log transform? (b) What are its...Ch. 12 - Prob. 40CECh. 12 - Prob. 41CECh. 12 - Prob. 42CECh. 12 - Prob. 43CECh. 12 - Prob. 44CECh. 12 - Prob. 45CECh. 12 - Prob. 46CECh. 12 - Prob. 47CECh. 12 - Prob. 48CECh. 12 - Prob. 49CECh. 12 - Prob. 50CECh. 12 - Prob. 51CECh. 12 - Prob. 52CECh. 12 - Prob. 53CECh. 12 - Prob. 54CECh. 12 - Prob. 55CECh. 12 - Prob. 56CECh. 12 - Prob. 57CECh. 12 - Prob. 58CECh. 12 - Prob. 59CECh. 12 - In the following regression, X = weekly pay, Y =...Ch. 12 - Prob. 61CECh. 12 - In the following regression, X = total assets (...Ch. 12 - Prob. 63CECh. 12 - Below are percentages for annual sales growth and...Ch. 12 - Prob. 65CECh. 12 - Prob. 66CECh. 12 - Prob. 67CECh. 12 - Simple regression was employed to establish the...Ch. 12 - Prob. 69CECh. 12 - Prob. 70CECh. 12 - Prob. 71CECh. 12 - Below are revenue and profit (both in billions)...Ch. 12 - Below are fitted regressions based on used vehicle...Ch. 12 - Below are results of a regression of Y = average...
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- For 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_forwardKindly compute the residual onlyarrow_forwardWhat is the difference between standardized and unstandardized regression coefficients? R2 is often used in connection with regression and is usually stated as explained variance (variance explained). What does this mean? What does it mean that the variance is "explained"? Give a brief but realistic example of a situation that would involve multicollinearity and explain why it is a problem.arrow_forward
- What is a residual for a multiple regression model and the data that is used to create it? Select one. Question 3 options: A statistic that explains the relationship between response and predictor variables The predicted value of the response variable using the multiple regression model A statistic that is used to evaluate the significance of the multiple regression model The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression modelarrow_forwardYou want to look at an ANOVA table of a regression in which a dependent variable is predicted using an intercept and one slope coefficient. Unfortunately, as you want to look at the table, you knock over your coffee mug which smudges out some of the numbers. Here is what you still can read: • n=7 • F-ratio = 15 • Residual sum of squares (RSS) = 16 • t-score of the slope coefficient = 3.873 How big is the explained sum of squares (ESS)? a 44 b 52 c 48 d 40 How big is the total sum of squares (TSS)? a 64 b 52 c 60 d 56 How big is the explained R-squared? a 0.7 b 0.75 c 0.8 d Cannot be determined What's the p-value for the F-ratio? a 0.012 b 0.024 c 0.036 d…arrow_forward21. Least-squares OK? Following is a residual plot produced by MINITAB. Was it appropriate to compute the least-squares regression line? Explain. Residuals Versus x -2 -3 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Residualarrow_forward
- A study was performed on 64 female college athletes. Researchers collected data on each female athlete's body weight (in pounds), height (in inches), lean body mass, age, and percent body fat. Researchers were interested in factors that may have an effect on female college athletes' percent body fat. The residual plot of the residuals versus predicted values is shown below. Residual Plot 5 residuals 0 -5 14 16 22 18 20 predicted values Which of the following statements is true based on the residual plot. (Check all that apply.) 24 The residuals are normally distributed since they are randomly scattered around the plot (except for one point with a high predicted value). The residuals are not normally distributed since the spread in the residuals is not the same for all predicted values. The constant variation condition may not be met since the spread in the residuals is not the same for all predicted values. There is one outlier with an unusually high predicted value. Because there is…arrow_forwardAnalysis of Variance Source DF SS MS Regression 1 Residual Error 13 0.2364 Total 14 11.3240 What is the value for MSR (Mean Square for Regression)?arrow_forwardModified True or False VIF is a measure of how much the variance of the estimated regression coefficients are inflated.arrow_forward
- What is a residual for a multiple regression model and the data that is used to create it? Select one. A A statistic that explains the relationship between response and predictor variables B The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression model C A statistic that is used to evaluate the significance of the multiple regression model D The predicted value of the response variable using the multiple regression modelarrow_forwardAnalysis of Variance Source DF SS MS Regression 1 Residual Error 13 0.2364 Total 14 11.3240 What is the value of SSE (Sums of Square Residual Error)?arrow_forward(a) How would you differentiate among multiple discriminant analysis, regression analysis, logistic regression analysis, and analysis of variance? (b) Explain at least two use cases from Marketing where discriminant analysis can be useful. Your answer needs to give the details of the scenario clearly. (c) Explain all the steps involved in Discriminant Analysis along with a detailed interpretation of the key outs of the model.arrow_forward
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