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Exam 17: A Roadmap for Analyzing Data

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TABLE 17-3 A financial analyst wanted to examine the relationship between salary (in $1,000)and 4 variables: age (X1 = Age),experience in the field (X2 = Exper),number of degrees (X3 = Degrees),and number of previous jobs in the field (X4 = Prevjobs).He took a sample of 20 employees and obtained the following Microsoft Excel output: SUMMARY OUTPUT Regression Statistics TABLE 17-3 A financial analyst wanted to examine the relationship between salary (in $1,000)and 4 variables: age (X<sub>1</sub> = Age),experience in the field (X<sub>2</sub> = Exper),number of degrees (X<sub>3</sub> = Degrees),and number of previous jobs in the field (X<sub>4</sub> = Prevjobs).He took a sample of 20 employees and obtained the following Microsoft Excel output: SUMMARY OUTPUT Regression Statistics ANOVA -Referring to Table 17-3,the analyst wants to use a t test to test for the significance of the coefficient of X<sub>3</sub>.For a level of significance of 0.01,the critical values of the test are ________. ANOVA TABLE 17-3 A financial analyst wanted to examine the relationship between salary (in $1,000)and 4 variables: age (X<sub>1</sub> = Age),experience in the field (X<sub>2</sub> = Exper),number of degrees (X<sub>3</sub> = Degrees),and number of previous jobs in the field (X<sub>4</sub> = Prevjobs).He took a sample of 20 employees and obtained the following Microsoft Excel output: SUMMARY OUTPUT Regression Statistics ANOVA -Referring to Table 17-3,the analyst wants to use a t test to test for the significance of the coefficient of X<sub>3</sub>.For a level of significance of 0.01,the critical values of the test are ________. TABLE 17-3 A financial analyst wanted to examine the relationship between salary (in $1,000)and 4 variables: age (X<sub>1</sub> = Age),experience in the field (X<sub>2</sub> = Exper),number of degrees (X<sub>3</sub> = Degrees),and number of previous jobs in the field (X<sub>4</sub> = Prevjobs).He took a sample of 20 employees and obtained the following Microsoft Excel output: SUMMARY OUTPUT Regression Statistics ANOVA -Referring to Table 17-3,the analyst wants to use a t test to test for the significance of the coefficient of X<sub>3</sub>.For a level of significance of 0.01,the critical values of the test are ________. -Referring to Table 17-3,the analyst wants to use a t test to test for the significance of the coefficient of X3.For a level of significance of 0.01,the critical values of the test are ________.

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Question 301

An airline wants to select a computer software package for its reservation system.Four software packages (1,2,3,and 4)are commercially available.An experiment is set up in which each package is used to make reservations for 5 randomly selected weeks and data on the number of passengers that are bumped over a month are collected.(A total of 20 weeks was included in the experiment.)The variance on the number of passengers that are bumped is found to be roughly the same for the 4 packages.Which of the following tests will be the most appropriate to find out if the mean number of passengers being bumped over a month is the same across the 4 packages?

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Question 302

TABLE 17-6 A weight-loss clinic wants to use regression analysis to build a model for weight loss of a client (measured in pounds).Two variables thought to affect weight loss are client's length of time on the weight-loss program and time of session.These variables are described below: Y = Weight loss (in pounds) X1 = Length of time in weight-loss program (in months) X2 = 1 if morning session,0 if not X3 = 1 if afternoon session,0 if not (Base level = evening session) Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Y = β0 + β1X1 + β2X2 + β3X3 + β4X1X2 + β5X1X3 + ε Partial output from Microsoft Excel follows: Regression Statistics TABLE 17-6 A weight-loss clinic wants to use regression analysis to build a model for weight loss of a client (measured in pounds).Two variables thought to affect weight loss are client's length of time on the weight-loss program and time of session.These variables are described below: Y = Weight loss (in pounds) X<sub>1 </sub>= Length of time in weight-loss program (in months) X<sub>2</sub> = 1 if morning session,0 if not X<sub>3</sub> = 1 if afternoon session,0 if not (Base level = evening session) Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>1</sub>X<sub>2</sub> + β<sub>5</sub>X<sub>1</sub>X<sub>3</sub> + ε Partial output from Microsoft Excel follows: Regression Statistics ANOVA F = 5.41118 Significance F = 0.040201 -Referring to Table 17-6,what null hypothesis would you test to determine whether the slope of the linear relationship between weight loss (Y)and time in the program (X<sub>1</sub>)varies according to time of session? ANOVA F = 5.41118 Significance F = 0.040201 TABLE 17-6 A weight-loss clinic wants to use regression analysis to build a model for weight loss of a client (measured in pounds).Two variables thought to affect weight loss are client's length of time on the weight-loss program and time of session.These variables are described below: Y = Weight loss (in pounds) X<sub>1 </sub>= Length of time in weight-loss program (in months) X<sub>2</sub> = 1 if morning session,0 if not X<sub>3</sub> = 1 if afternoon session,0 if not (Base level = evening session) Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>1</sub>X<sub>2</sub> + β<sub>5</sub>X<sub>1</sub>X<sub>3</sub> + ε Partial output from Microsoft Excel follows: Regression Statistics ANOVA F = 5.41118 Significance F = 0.040201 -Referring to Table 17-6,what null hypothesis would you test to determine whether the slope of the linear relationship between weight loss (Y)and time in the program (X<sub>1</sub>)varies according to time of session? -Referring to Table 17-6,what null hypothesis would you test to determine whether the slope of the linear relationship between weight loss (Y)and time in the program (X1)varies according to time of session?

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