Exam 17: Multiple Regression
Exam 1: What Is Statistics46 Questions
Exam 2: Graphical Descriptive Techniques 194 Questions
Exam 3: Graphical Descriptive Techniques 2156 Questions
Exam 4: Numerical Descriptive Techniques275 Questions
Exam 5: Data Collection and Sampling84 Questions
Exam 6: Probability240 Questions
Exam 7: Random Variables and Discrete Probability Distributions283 Questions
Exam 8: Continuous Probability Distributions224 Questions
Exam 9: Sampling Distributions156 Questions
Exam 10: Introduction to Estimation154 Questions
Exam 11: Introduction to Hypothesis Testing189 Questions
Exam 12: Inference About a Population153 Questions
Exam 13: Inference About Comparing Two Populations170 Questions
Exam 14: Analysis of Variance157 Questions
Exam 15: Chi-Squared Tests179 Questions
Exam 16: Simple Linear Regression and Correlation304 Questions
Exam 17: Multiple Regression160 Questions
Exam 18: Model Building148 Questions
Exam 19: Nonparametric Statistics175 Questions
Exam 20: Time-Series Analytics and Forecasting225 Questions
Exam 21: Statistical Process Control140 Questions
Exam 22: Decision Analysis123 Questions
Exam 23: Conclusion47 Questions
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In multiple regression analysis,the adjusted coefficient of determination is adjusted for the number of independent variables and the sample size.
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In a multiple regression analysis involving 50 observations and 5 independent variables,the total variation in y is 475 and SSE = 71.25.Then,the coefficient of determination is 0.85.
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Discuss two indicators that can be found in an analysis that suggest multicollinearity is present.
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A good indicator of multicollinearity is a large F-statistic,but small t-statistics.A related clue to the presence of multicollinearity is an independent variable known to be an important predictor that ends up having a regression coefficient that is not significant.Another clue is when a regression coefficient exhibits the wrong sign.Or when an independent variable is added or deleted,the regression coefficients for the other variables change drastically.
Life Expectancy
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (x1),the cholesterol level (x2),and the number of points that the individual's blood pressure exceeded the recommended value (x3).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below. THE REGRESSION EQUATION IS y = 55.8 + 1.79x1− 0.021x2− 0.061x3
S = 9.47 R−Sq = 22.5% ANALYSIS OF VARIANCE
-{Life Expectancy Narrative} Is there enough evidence at the 5% significance level to infer that the model is useful in predicting length of life?


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In a multiple regression analysis involving 40 observations and 5 independent variables,the following statistics are given: Total variation in y = 350 and SSE = 50.Then,the coefficient of determination is:
(Multiple Choice)
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A multiple regression model has the form
.The coefficient b1 is interpreted as the change in the average value of y per unit change in ________ holding ________ constant.

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Life Expectancy
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (x1),the cholesterol level (x2),and the number of points that the individual's blood pressure exceeded the recommended value (x3).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below. THE REGRESSION EQUATION IS y = 55.8 + 1.79x1− 0.021x2− 0.061x3
S = 9.47 R−Sq = 22.5% ANALYSIS OF VARIANCE
-{Life Expectancy Narrative} Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related?


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Multiple regression has four requirements for the error variable.One is that the probability distribution of the error variable is ____________________.
(Short Answer)
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A small value of F indicates that most of the variation in y is explained by the regression equation and that the model is useful.
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Real Estate Builder
A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA
-{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which all explanatory variables are significant individually: α = .01,.05,.10,or .15?


(Short Answer)
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If the value of the Durbin-Watson test statistic,d,satisfies the inequality d > 4 −dL,we conclude that positive first-order autocorrelation exists.
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In reference to the equation
,the value 0.12 is the average change in y per unit change in x1,when x2 is held constant.

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If the value of the Durbin-Watson test statistic,d,satisfies the inequalities d < dL or d > 4 −dL,where dL and dU are the critical values of d,we conclude that autocorrelation exists.
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In testing the significance of a multiple regression model with three independent variables,the null hypothesis is
.

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Some of the requirements for the error variable in a multiple regression model are that the probability distribution is ____________________ with a mean of ____________________.
(Short Answer)
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If the Durbin-Watson statistic has a value close to 4,which assumption is violated?
(Multiple Choice)
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A multiple regression model is assessed to be good if the error sum of squares SSE and the standard error of estimate sε are both small,the coefficient of determination R2 is close to 1,and the value of the test statistic F is large.
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Consider the following statistics of a multiple regression model: Total variation in y = 1000,SSE = 300,n = 50,and k = 4.
a.Determine the standard error of estimate.
b.Determine the coefficient of determination.
c.Determine the F-statistic.
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A high correlation between two independent variables is an indication of ____________________.
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