Introductory Statistics (10th Edition)
10th Edition
ISBN: 9780321989178
Author: Neil A. Weiss
Publisher: PEARSON
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Textbook Question
Chapter B.4, Problem 75E
Explain why the interpretation of the regression coefficients is difficult when the predictor variables are highly intercorrelated.
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when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks.
The research question is
How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)?
Conduct a multiple regression analysis to answer the following questions:
What is the relationship of age, number of years, and social support with work stress?
Is the regression significant? If yes, what does it indicate?
Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks.
The research question is
How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)?
Conduct a multiple regression analysis to answer the following questions:
What is the regression equation for all the predictors?
Write a results section based on your analysis that answers the research question.
Chapter B Solutions
Introductory Statistics (10th Edition)
Ch. B.1 - Regarding the regression of a response variable,...Ch. B.1 - Fill in the blanks. a. The assumption that all...Ch. B.1 - Answer true or false to each of the following...Ch. B.1 - Prob. 4ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Prob. 6ECh. B.1 - Prob. 7ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...
Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Prob. 12ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Consider the scatterplot of y versus x in Output...Ch. B.1 - Consider the scatterplot of y versus x in Output...Ch. B.1 - Prob. 17ECh. B.1 - Prob. 18ECh. B.1 - If one or both of the assumptions of...Ch. B.1 - Prob. 20ECh. B.1 - Prob. 21ECh. B.1 - Prob. 22ECh. B.1 - Prob. 23ECh. B.1 - Gasoline Mileage Ratings. Gasoline mileage and...Ch. B.1 - Hip Fracture Rates. In the paper Very Low Rates of...Ch. B.1 - Prob. 26ECh. B.1 - Prob. 27ECh. B.1 - Prob. 28ECh. B.1 - Prob. 29ECh. B.1 - Gasoline Mileage Ratings. Refer to Exercise B.24,...Ch. B.1 - Hip Fracture Rates. Refer to Exercise B.25, where...Ch. B.1 - Drosophila Life-span. In the paper Extended...Ch. B.1 - Protein Content of Wheat. In their text, Methods...Ch. B.1 - Pine Tree Volume. Table B.2 on page B-5 provides...Ch. B.2 - Give an example of a. a second-degree polynomial...Ch. B.2 - In the polynomial regression equation y = 8 + 3x ...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Explain why it is difficult to interpret the...Ch. B.2 - Fill in the blanks. a. A predictor variable is...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Refer to the scatterplots in Outputs B.32(a) and...Ch. B.2 - Fill in the blanks. a. In the _______ method for...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Stopping Distance. In their text Methods of...Ch. B.2 - Hour of Birth. In the paper increased Frequency of...Ch. B.2 - Silica Gel. Silica gel is a substance that absorbs...Ch. B.2 - Note: The data for the Using Technology exercises...Ch. B.2 - Hour of Birth. Refer to Exercise B.45, where the...Ch. B.2 - Silica Gel. Refer to Exercise B.46, where the...Ch. B.2 - Gasoline Mileage Ratings. Refer to Exercise B.24...Ch. B.2 - Protein Content of Wheat. Refer to Exercise B.33...Ch. B.2 - Satellite Orbits. Each issue of the magazine Ad...Ch. B.2 - Pine Tree Volume. In Example B.6 on page B-4, we...Ch. B.3 - Explain the difference between a quantitative...Ch. B.3 - In predicting a person's income, identify two...Ch. B.3 - In predicting the change in blood pressure for...Ch. B.3 - Fill in the blanks. a. A ___ predictor variable is...Ch. B.3 - Prob. 59ECh. B.3 - Answer true or false to each of the following...Ch. B.3 - For the regression equation y = 15 + 2x1 + 4x2 ...Ch. B.3 - Refer to Exercise B.61: a. Do the slopes of the...Ch. B.3 - Consider the regression equation y = 0 + 1 x1+ 2x2...Ch. B.3 - Prob. 64ECh. B.3 - Prob. 65ECh. B.3 - Prob. 66ECh. B.3 - Home Sale Prices. Refer to Example B.18 on page...Ch. B.3 - Mental Tasks and Drugs. In the text Statistical...Ch. B.3 - Gasoline Mileage Ratings. Refer to Exercise B.66...Ch. B.3 - Home Sale Prices. Refer to Exercise B.67 regarding...Ch. B.3 - Mental Tasks and Drugs. Refer to Exercise B.68...Ch. B.3 - Hip Fracture Rates. Refer to Exercise B.25 on page...Ch. B.3 - Television Viewing. The results of a study on...Ch. B.3 - Glue Strength. In the text Quality Control and...Ch. B.4 - Explain why the interpretation of the regression...Ch. B.4 - Answer true or false to each of the following...Ch. B.4 - Explain what is meant by multicollinearity.Ch. B.4 - Fill in the blanks. a. Consider a regression model...Ch. B.4 - Prob. 79ECh. B.4 - Prob. 80ECh. B.4 - Fill in the blanks. a. If predictor variable x1...Ch. B.4 - Answer true or false to each of the following...Ch. B.4 - State four ways to detect the presence of...Ch. B.4 - Prob. 84ECh. B.4 - Prob. 85ECh. B.4 - Prob. 86ECh. B.4 - Prob. 87ECh. B.4 - Prob. 88ECh. B.4 - Graduation Rates. Refer to Exercise B.86, where we...Ch. B.4 - Prob. 90ECh. B.4 - Gasoline Mileage Ratings. Refer to Exercise B.84,...Ch. B.4 - Graduation Rules. Refer to Exercise B.86, where we...Ch. B.5 - Explain what is meant by the variable selection...Ch. B.5 - Prob. 94ECh. B.5 - Fill in the blanks. a. In the forward selection...Ch. B.5 - Prob. 96ECh. B.5 - Answer true or false to each of the following...Ch. B.5 - Prob. 98ECh. B.5 - Prob. 99ECh. B.5 - Prob. 100ECh. B.5 - Prob. 101ECh. B.5 - Suppose that x1, x2, x3, and x4 are predictor...Ch. B.5 - Prob. 103ECh. B.5 - Graduation Rates. Refer to Exercise B.92 on page...Ch. B.5 - Home Sale Prices. In Example B. 18 on page B-67,...Ch. B.5 - Home Sale Prices. In Example B.18 on page B-67, we...Ch. B.5 - Infant Mortality Rates. In the article Children's...Ch. B.6 - Consider a multiple linear regression relating the...Ch. B.6 - Prob. 109ECh. B.6 - Prob. 110ECh. B.6 - Answer true or false to each of the following...Ch. B.6 - Explain the similarities and differences between...Ch. B.6 - Fill in the blanks. a. In the Mallows Cp...Ch. B.6 - Answer true or false to each of the following...Ch. B.6 - Gasoline Mileage Ratings. Refer to Exercise B.84...Ch. B.6 - Advertising and Sales. Refer to Exercise B.85 on...Ch. B.6 - Graduation Rates. Refer to Exercise B.86 on page...Ch. B.6 - Suppose that x1, x2, x3, and x4 are predictor...Ch. B.6 - Suppose that x1 x2, x3, and x4 are predictor...Ch. B.6 - Gasoline Mileage Ratings. Refer to Exercise B.91...Ch. B.6 - Graduation Rates. Refer to Exercise B.92 on page...Ch. B.6 - Home Sale Prices. Refer to Exercise B.105 on page...Ch. B.6 - Body Fat. Refer to Exercise B.106 on page B-143,...Ch. B.6 - Infant Mortality Rates. Refer to Exercise B.107 on...Ch. B.7 - List six problems that can arise in the collection...Ch. B.7 - Prob. 126ECh. B.7 - Prob. 127ECh. B.7 - Give an example of how a nonrepresentative sample...Ch. B.7 - Discuss the effect on a regression analysis of not...Ch. B.7 - Explain how multicollinearity can adversely affect...Ch. B.7 - Briefly describe what is meant by the problem of...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Prob. 133ECh. B.7 - Discuss the advantages of using data collected...Ch. B.7 - Describe the potential effects of outliers on...Ch. B.7 - Prob. 136ECh. B.7 - Regarding regression analysis: a. What assumptions...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Discuss what G. E. P. Box might have meant when he...Ch. B.7 - Regarding model validation in regression: a. What...Ch. B - Explain what is meant when we say that a nonlinear...Ch. B - Answer true or false to the following statements...Ch. B - Prob. 3RPCh. B - Prob. 4RPCh. B - Answer true or false to each of the following...Ch. B - Paper Strength. In their text, Introduction to...Ch. B - Answer true or false to each of the following...Ch. B - Prob. 8RPCh. B - Explain what is meant when we say that a...Ch. B - OUTPUT B.95 Output for Problem 10 Regression...Ch. B - In regressing a response variable on several...Ch. B - Answer true or false to each of the following...Ch. B - Fill in the blanks. a. Multicollinearity is...Ch. B - Prob. 14RPCh. B - Explain why selecting a regression equation using...Ch. B - Answer true or false to each of the following...Ch. B - Fill in the blanks. a. In the _____ method, we...Ch. B - Patent Production. In the report The State New...Ch. B - Prob. 19RPCh. B - Prob. 20RPCh. B - Patent Production. Refer to Problem 18. where we...Ch. B - Prob. 22RPCh. B - Prob. 23RPCh. B - What are the possible consequences of the presence...Ch. B - Windmill Output. Refer to Problem 3, where we...Ch. B - Paper Strength. Refer to Problem 6, where we...Ch. B - Diabetes. Refer to Problem 10, where we considered...Ch. B - Hospital Stalling. Refer to Problem 14, where we...Ch. B - Patent Production. Refer to Problem 18, where we...Ch. B - Patent Production. Refer to Problem 29, where we...Ch. B - Recall from Chapter 1 of your text that the Focus...Ch. B - At the beginning of this module on page B-l, we...
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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
- Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: State the hypothesis for this study.arrow_forwardWhat does it mean for a regression line to be the "best-fit" line.arrow_forwardA county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model, y = b₁x + bowhere y = appraised value of the house (in $thousands) and x = number of rooms. Using data collected for a sample of n=74 houses in East Meadow, the following results were obtained: y=74.80+ 17.80x Give a practical interpretation of the estimate of the slope of the least squares line. For each additional room in the house, we estimate the appraised value to increase $74,800. 1000 For each additional dollar of appraised value, we estimate the number of rooms in the house to increase by 17.80 rooms. For a house with 0 rooms, we estimate the appraised value to be $74,800. For each additional room in the house, we estimate the…arrow_forward
- Why is it necessary that the variables are significantly correlated before performing regression analysis?arrow_forwardExplain why it is not a good idea to exclude an intercept, b0 , from any linear regression model?arrow_forwardBill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. Conduct a multiple regression analysis to answer the following questions: What is the relationship of age, number of years, and social support with work stress? Is the regression significant? If yes, what does it indicate? What is the regression equation for all the predictors? Write a results section based on your analysis that answers the research question. * last person got this wrong*arrow_forward
- An industrial psychologist examined the number of absences for employees in Company A. She wanted to look into a possibility that the number of absences may regressed onto the level of stress that employees feel. The following data set below indicates perceived level of stress (Variable X) for a sample of 10 employees in Company A and the number of their absences in one month (Variable Y). A greater number for X indicates a higher level of stress. If you find a linear regression equation, what is the regression slope from the data below? Enter the number using decimal points (use two decimal points). Round to the closest second decimal point. For instance, if your answer is 0.3456, enter "0.35" Level of Stress (X) 2 1 3 7 2 5 2 4 8 6 # of Absences (Y) 4 7 6 9 6 8 7 10 11 7arrow_forwardThe St. Lucian Government is interested in predicting the number of weekly riders on the public buses using the following variables: • • • • Price of bus trips per weekThe population in the cityThe monthly income of ridersAverage rate to park your personal vehicle Determine the multiple regression equation for the data. What is the predicted value of the number of weekly riders if: price of bus trips per week = $24; population = $2,000,000; the monthly income of riders = $13,500; and average rate to park your personal vehicle = $150. Interpret the coefficient of determination.arrow_forwardIn general, what are some problems with using regression to measure causal effects?arrow_forward
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