Deck 15: Inference With Regression Models
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Deck 15: Inference With Regression Models
1
The term BLUE stands for Best Linear Unbiased Estimator.
True
2
_______ plots can be used to detect common violations,and they can be used to detect outliers.
Residual
3
Consider the following simple linear regression model: y = β0 + β1x + ε.When determining whether there is a one-to-one relationship between x and y,the null hypothesis takes the form ______________.
A) H0:β1 = 0
B) H0:β1 = 1
C) H0:b1 = 0
D) H0:b1 = 1
A) H0:β1 = 0
B) H0:β1 = 1
C) H0:b1 = 0
D) H0:b1 = 1
B
4
Consider the following simple linear regression model: y = β0 + β1x + ε.When determining whether x significantly influences y,the null hypothesis takes the form ______________.
A) H0:β1 = 0
B) H0:β1 = 1
C) H0:b1 = 0
D) H0:b1 = 1
A) H0:β1 = 0
B) H0:β1 = 1
C) H0:b1 = 0
D) H0:b1 = 1
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5
With the partial F test,we basically analyze the ratio of (SSER - SSEU)to ______.
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6
Conditional on x1,x2,... ,xk,the error term ε is ________ distributed.
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7
If in the multiple linear model the slope coefficient βi is negative,it suggests an inverse (negative)relationship between the explanatory variable xi and the response variable y.
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8
A wavelike movement in residuals suggests positive serial correlation.
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9
It is common to refer to the interval estimate for an individual value of y as the _________ interval.
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10
The test statistic for testing the individual significance is assumed to follow the t distribution with n - k - 2 degrees of freedom,where n is the sample size and k is the number of explanatory variables.
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11
The F test can be applied for any number of linear restrictions;the resulting test is often referred to as the _____ F test.
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12
The term multicollinearity refers to the condition when the variance of the error term,conditional on x1,x2,…,xn,is the same for all observations.
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13
Consider the following simple linear regression model: y = β0 + β1x + ε.When determining whether there is a positive linear relationship between x and y,the alternative hypothesis takes the form ______________.
A) HA:β1 = 0
B) HA:β1 > 1
C) HA:β1 < 0
D) HA:b1 > 1
A) HA:β1 = 0
B) HA:β1 > 1
C) HA:β1 < 0
D) HA:b1 > 1
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14
The alternative hypothesis for the test of joint significance is specified as: HA: At least two βj ≠ 0.
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15
The restricted model is a reduced model where we estimate the coefficients that are restricted under the null hypothesis.
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16
One of the required assumptions of regression analysis states that the error term has a(an)________ value of zero.
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17
When some explanatory variables of a regression model are strongly correlated,this phenomenon is called serial correlation.
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18
If the confidence interval does not contain the value zero,then the ________ variable associated with the regression coefficient is significant.
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19
A crucial assumption in a regression model is that the error term is not correlated with any of the explanatory variables.
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20
The _________ model is a complete model that imposes no restrictions on the coefficients.
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21
The accompanying table shows the regression results when estimating y = β0 + β1x + ε.
Which of the following is the value of the test statistic when testing whether x significantly influences y?
A) 0.66
B) 1.42
C) 1.96
D) 2.25

A) 0.66
B) 1.42
C) 1.96
D) 2.25
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22
Refer to the portion of regression results in the accompanying table.
When testing the overall significance of the regression model at the 5% level given a critical value of F0.05, (2.20) = 3.49,the decision is to _____________________________________________________________.
A) reject H0 and conclude that the explanatory variables are jointly significant.
B) not reject H0 and conclude that the explanatory variables are jointly significant.
C) reject H0 and conclude that the explanatory variables are not jointly significant.
D) not reject H0 and conclude that the explanatory variables are not jointly significant.

A) reject H0 and conclude that the explanatory variables are jointly significant.
B) not reject H0 and conclude that the explanatory variables are jointly significant.
C) reject H0 and conclude that the explanatory variables are not jointly significant.
D) not reject H0 and conclude that the explanatory variables are not jointly significant.
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23
Which of the following is the 95% confidence interval for the regression coefficient β1,if df = 30,b1= −2 and ![<strong>Which of the following is the 95% confidence interval for the regression coefficient β<sub>1</sub>,if df = 30,b<sub>1</sub>= −2 and </strong> A) [−5.00,−1.00] B) [−7.88,3.88] C) [−7.09,3.09] D) [−8.13,4.13]](https://storage.examlex.com/TB4266/11eab0ce_309c_b8ab_a083_d9b7a254465f_TB4266_11.jpg)
A) [−5.00,−1.00]
B) [−7.88,3.88]
C) [−7.09,3.09]
D) [−8.13,4.13]
![<strong>Which of the following is the 95% confidence interval for the regression coefficient β<sub>1</sub>,if df = 30,b<sub>1</sub>= −2 and </strong> A) [−5.00,−1.00] B) [−7.88,3.88] C) [−7.09,3.09] D) [−8.13,4.13]](https://storage.examlex.com/TB4266/11eab0ce_309c_b8ab_a083_d9b7a254465f_TB4266_11.jpg)
A) [−5.00,−1.00]
B) [−7.88,3.88]
C) [−7.09,3.09]
D) [−8.13,4.13]
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24
Given the following portion of regression results,which of the following is the value of the F2,20 test statistic? 
A) 1.96
B) 3.49
C) 8.04
D) 10

A) 1.96
B) 3.49
C) 8.04
D) 10
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25
The accompanying table shows the regression results when estimating y = β0 + β1x + ε.
Is x significantly related to y at the 5% significance level?
A) Yes,because the p-value of 0.0745 is greater than 0.05.
B) No,because the p-value of 0.0745 is greater than 0.05.
C) Yes,because the slope coefficient of 1.417 is less than the test statistic of 2.25.
D) No,because the slope coefficient of 1.417 is less than the test statistic of 2.25.

A) Yes,because the p-value of 0.0745 is greater than 0.05.
B) No,because the p-value of 0.0745 is greater than 0.05.
C) Yes,because the slope coefficient of 1.417 is less than the test statistic of 2.25.
D) No,because the slope coefficient of 1.417 is less than the test statistic of 2.25.
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26
Given the following portion of regression results,which of the following conclusions is true with regard to the F test at the 5% significance level? 
A) Neither of the explanatory variables is related to the response variable.
B) Both of the explanatory variables are related to the response variable.
C) Exactly one of the explanatory variables is related to the response variable.
D) At least one of the explanatory variables is significantly related to the response variable.

A) Neither of the explanatory variables is related to the response variable.
B) Both of the explanatory variables are related to the response variable.
C) Exactly one of the explanatory variables is related to the response variable.
D) At least one of the explanatory variables is significantly related to the response variable.
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27
When estimating y = β0 + β1x1 + β2x2 + β3x3 + ε,you wish to test H0: β1 = β2 = 0 versus HA: At least one βi = 0.The value of the test statistic is F(2,20) = 2.50 and its associated p-value is 0.1073.At the 5% significance level,the conclusion is to ____________________________________________________________.
A) reject the null hypothesis and conclude that x1 and x2 are jointly significant
B) reject the null hypothesis and conclude that x1 and x2 are not jointly significant
C) not reject the null hypothesis and conclude that x1 and x2 are jointly significant
D) not reject the null hypothesis and conclude that x1 and x2 are not jointly significant
A) reject the null hypothesis and conclude that x1 and x2 are jointly significant
B) reject the null hypothesis and conclude that x1 and x2 are not jointly significant
C) not reject the null hypothesis and conclude that x1 and x2 are jointly significant
D) not reject the null hypothesis and conclude that x1 and x2 are not jointly significant
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28
Given the following portion of regression results,which of the following is the value of the F(2,20) test statistic? 
A) 1.96
B) 2.59
C) 3.49
D) 10

A) 1.96
B) 2.59
C) 3.49
D) 10
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29
When testing linear restrictions,the test statistic is assumed to follow the y = β0 + β1x1 + β2x2 + β3x3 + ε,you wish to test H0: β1 = β2 versus HA: β1 ≠ β2 The value of the test statistic is F(1,30) = 7.75 and its associated p-value is 0.0092.At the 1% significance level,the conclusion is to ____________________________________________________________________________.
A) reject the null hypothesis and conclude that the influence of x1 and x2 on y is the same
B) reject the null hypothesis and conclude that the influence of x1 and x2 on y is not the same
C) not reject the null hypothesis and conclude that the influence of x1 and x2 on y is the same
D) not reject the null hypothesis and conclude that the influence of x1 and x2 on y is not the same
A) reject the null hypothesis and conclude that the influence of x1 and x2 on y is the same
B) reject the null hypothesis and conclude that the influence of x1 and x2 on y is not the same
C) not reject the null hypothesis and conclude that the influence of x1 and x2 on y is the same
D) not reject the null hypothesis and conclude that the influence of x1 and x2 on y is not the same
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30
A sample of 200 monthly observations is used to run a simple linear regression: Returns = β0 + β1 Leverage + ε.A 5% level of significance is used to study if leverage has a significant influence on returns.The value of the test statistic for the regression coefficient of Leverage is calculated as t198 = -1.09,with an associated p-value of 0.2770.The correct decision is to __________________________________________________________.
A) reject the null hypothesis and conclude that leverage significantly explains returns
B) reject the null hypothesis and conclude that leverage does not significantly explain returns
C) not reject the null hypothesis and conclude that leverage does not significantly explain returns
D) not reject the null hypothesis and conclude that leverage significantly explains returns
A) reject the null hypothesis and conclude that leverage significantly explains returns
B) reject the null hypothesis and conclude that leverage does not significantly explain returns
C) not reject the null hypothesis and conclude that leverage does not significantly explain returns
D) not reject the null hypothesis and conclude that leverage significantly explains returns
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31
Excel and virtually all other statistical packages report the p-value ____________________________________.
A) for a two-tailed test that assesses whether the regression coefficient differs from one
B) for a right-tailed test that assesses whether the regression coefficient is greater than zero
C) for a two-tailed test that assesses whether the regression coefficient differs from zero
D) for a left-tailed test that assesses whether the regression coefficient is less than zero
A) for a two-tailed test that assesses whether the regression coefficient differs from one
B) for a right-tailed test that assesses whether the regression coefficient is greater than zero
C) for a two-tailed test that assesses whether the regression coefficient differs from zero
D) for a left-tailed test that assesses whether the regression coefficient is less than zero
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32
In regression,the two types of interval estimates concerning y are called _________________________________.
A) significance interval and prediction interval
B) confidence interval and significance interval
C) confidence interval and prediction interval
D) significance interval and frequency interval
A) significance interval and prediction interval
B) confidence interval and significance interval
C) confidence interval and prediction interval
D) significance interval and frequency interval
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33
The accompanying table shows the regression results when estimating y = β0 + β1x + ε.
When testing whether the slope coefficient differs from 1,the value of the test statistic is ____.
A) 0.66
B) 1.42
C) 1.96
D) 2.25

A) 0.66
B) 1.42
C) 1.96
D) 2.25
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34
In regression,the predicted values concerning y are subject to _____________.
A) kurtosis
B) skewness
C) mean deviation
D) sampling variation
A) kurtosis
B) skewness
C) mean deviation
D) sampling variation
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35
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2 + β3x3 + ε.
At the 5% significance level,which of the following explanatory variable(s)is(are)individually significant?
A) Only x1
B) Only x3
C) x1 and x2
D) x2 and x3

A) Only x1
B) Only x3
C) x1 and x2
D) x2 and x3
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36
Refer to the portion of regression results in the accompanying table.
When testing the overall significance of the regression model at the 5% level given a critical value of F0.05, (2,20) = 3.49,the decision is to _______________________________________________________.
A) reject H0 and conclude that the explanatory variables are jointly significant
B) not reject H0 and conclude that the explanatory variables are jointly significant
C) reject H0 and conclude that the explanatory variables are not jointly significant
D) not reject H0 and conclude that the explanatory variables are not jointly significant

A) reject H0 and conclude that the explanatory variables are jointly significant
B) not reject H0 and conclude that the explanatory variables are jointly significant
C) reject H0 and conclude that the explanatory variables are not jointly significant
D) not reject H0 and conclude that the explanatory variables are not jointly significant
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37
For a given confidence level,the prediction interval is always wider than the confidence interval because _________________________________________________________________________________.
A) the confidence interval is for a particular value of y rather than for the expected value E(y)
B) the prediction interval is for a particular value of y rather than for the expected value E(y)
C) the confidence interval is for a particular value of x rather than for the expected value E(x)
D) the prediction interval is for a particular value of x rather than for the expected value E(x)
A) the confidence interval is for a particular value of y rather than for the expected value E(y)
B) the prediction interval is for a particular value of y rather than for the expected value E(y)
C) the confidence interval is for a particular value of x rather than for the expected value E(x)
D) the prediction interval is for a particular value of x rather than for the expected value E(x)
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38
Consider the following simple linear regression model: y = β0 + β1x + ε.When determining whether there is a negative linear relationship between x and y,the alternative hypothesis takes the form ______________.
A) HA:β1 = 0
B) HA:β1 > 0
C) HA:b1 < 0
D) HA:b1 > 0
A) HA:β1 = 0
B) HA:β1 > 0
C) HA:b1 < 0
D) HA:b1 > 0
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39
Given the following portion of regression results,which of the following conclusions is true with regard to the F test at the 5% significance level? 
A) Neither of the explanatory variables is significantly related to the response variable.
B) Both of the explanatory variables are significantly related to the response variable.
C) Exactly one of the explanatory variables is significantly related to the response variable.
D) At least one of the explanatory variables is significantly related to the response variable.

A) Neither of the explanatory variables is significantly related to the response variable.
B) Both of the explanatory variables are significantly related to the response variable.
C) Exactly one of the explanatory variables is significantly related to the response variable.
D) At least one of the explanatory variables is significantly related to the response variable.
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40
When testing r linear restrictions imposed on the model y = β0 + β1x1 + ...+ βkxk + ε,the test statistic is assumed to follow the F(df1,df2)distribution with ____________________.
A) df1 = k and df2 = n - k - 1
B) df1 = k - 1 and df2 = n - k - 1
C) df1 = r and df2 = n - k
D) df1 = r and df2 = n - k - 1
A) df1 = k and df2 = n - k - 1
B) df1 = k - 1 and df2 = n - k - 1
C) df1 = r and df2 = n - k
D) df1 = r and df2 = n - k - 1
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41
Which of the following violates the assumptions of regression analysis?
A) The error term is normally distributed.
B) The error term has a zero mean.
C) The error term is correlated with an explanatory variable.
D) The error term has a constant variance.
A) The error term is normally distributed.
B) The error term has a zero mean.
C) The error term is correlated with an explanatory variable.
D) The error term has a constant variance.
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42
Multicollinearity is suspected when ________________________________________________.
A) there is a low R2 coupled with significant explanatory variables
B) there is a high R2 coupled with significant explanatory variables
C) there is a low R2 coupled with insignificant explanatory variables
D) there is a high R2 coupled with insignificant explanatory variables
A) there is a low R2 coupled with significant explanatory variables
B) there is a high R2 coupled with significant explanatory variables
C) there is a low R2 coupled with insignificant explanatory variables
D) there is a high R2 coupled with insignificant explanatory variables
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43
When confronted with multicollinearity,a good remedy is to _______________________ if we can justify its redundancy.
A) add one more collinear variable
B) drop one of the collinear variables
C) remove both the collinear variables
D) add as many collinear variables as possible
A) add one more collinear variable
B) drop one of the collinear variables
C) remove both the collinear variables
D) add as many collinear variables as possible
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44
A researcher gathers data on 25 households and estimates the following model: Expenditure = β0 + β1 Income + ε.A residual plot of the estimated model is shown in the accompanying graph.
Which of the following can be inferred from the residual plot?
A) The residuals have little variation.
B) The residuals do not exhibit any pattern.
C) The residuals seem to fan out across the horizontal axis.
D) The residuals are evenly distributed across the horizontal axis.

A) The residuals have little variation.
B) The residuals do not exhibit any pattern.
C) The residuals seem to fan out across the horizontal axis.
D) The residuals are evenly distributed across the horizontal axis.
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45
One of the assumptions of regression analysis is ___________________________________________________.
A) there is perfect multicollinearity among some explanatory variables
B) there is no perfect multicollinearity among any explanatory variables
C) there is some degree of multicollinearity among some explanatory variables
D) None of these choices is correct.
A) there is perfect multicollinearity among some explanatory variables
B) there is no perfect multicollinearity among any explanatory variables
C) there is some degree of multicollinearity among some explanatory variables
D) None of these choices is correct.
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46
A sports analyst wants to exam the factors that may influence a tennis player's chances of winning.Over four tournaments,he collects data on 30 tennis players and estimates the following model: Win = β0 + β1 Double Faults + β2Aces + ε,where Win is the proportion of winning,Double Faults is the percentage of double faults made,and Aces is the number of aces.A portion of the regression results are shown in the accompanying table.
Is the relationship between Win and Aces significant at the 5% significance level?
A) No,because the relevant p-value is less than 0.05.
B) Yes,because the relevant p-value is less than 0.05.
C) No,because the relevant p-value is greater than 0.05.
D) Yes,because the relevant p-value is greater than 0.05.

A) No,because the relevant p-value is less than 0.05.
B) Yes,because the relevant p-value is less than 0.05.
C) No,because the relevant p-value is greater than 0.05.
D) Yes,because the relevant p-value is greater than 0.05.
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47
A sports analyst wants to exam the factors that may influence a tennis player's chances of winning.Over four tournaments,he collects data on 30 tennis players and estimates the following model: Win = β0 + β1 Double Faults + β2Aces + ε,where Win is the proportion of winning,Double Faults is the percentage of double faults made,and Aces is the number of aces.A portion of the regression results are shown in the accompanying table.
When testing whether the explanatory variables are jointly significant at the 5% significance level,he _______________________________________________________________________.
A) rejects H0,and concludes that the explanatory variables are jointly significant
B) does not reject H0,and concludes that the explanatory variables are jointly significant
C) rejects H0,and concludes that the explanatory variables are not jointly significant
D) does not reject H0,and concludes that the explanatory variables are not jointly significant

A) rejects H0,and concludes that the explanatory variables are jointly significant
B) does not reject H0,and concludes that the explanatory variables are jointly significant
C) rejects H0,and concludes that the explanatory variables are not jointly significant
D) does not reject H0,and concludes that the explanatory variables are not jointly significant
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48
A sports analyst wants to exam the factors that may influence a tennis player's chances of winning.Over four tournaments,he collects data on 30 tennis players and estimates the following model: Win = β0 + β1 Double Faults + β2Aces + ε,where Win is the proportion of winning,Double Faults is the percentage of double faults made,and Aces is the number of aces.A portion of the regression results are shown in the accompanying table.
When testing whether the explanatory variables jointly influence the response variable,the null hypothesis is ______________________.
A) H0:β1 = β2 = 0
B) H0:β1 + β2 = 0
C) H0:β0 = β1 = β2 = 0
D) H0:β0 + β1 + β2 + 0

A) H0:β1 = β2 = 0
B) H0:β1 + β2 = 0
C) H0:β0 = β1 = β2 = 0
D) H0:β0 + β1 + β2 + 0
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49
A marketing analyst wants to examine the relationship between sales (in $1,000s)and advertising (in $100s)for firms in the food and beverage industry and so collects monthly data for 25 firms.He estimates the model: Sales = β0 + β1 Advertising + ε.The following table shows a portion of the regression results.
Which of the following are the competing hypotheses used to test whether the slope coefficient differs from 3?
A) H0:b1 = 3;HA:b1 ≠ 3
B) H0:b1 = 2.88;HA:b1 ≠ 2.88
C) H0:β1 = 3;HA:β1 ≠ 3
D) H0:β1 = 2.88;HA:β1 ≠ 2.88

A) H0:b1 = 3;HA:b1 ≠ 3
B) H0:b1 = 2.88;HA:b1 ≠ 2.88
C) H0:β1 = 3;HA:β1 ≠ 3
D) H0:β1 = 2.88;HA:β1 ≠ 2.88
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50
A marketing analyst wants to examine the relationship between sales (in $1,000s)and advertising (in $100s)for firms in the food and beverage industry and so collects monthly data for 25 firms.He estimates the model: Sales = β0 + β1 Advertising + ε.The following table shows a portion of the regression results.
When testing whether Advertising is significant at the 10% significance level,the conclusion is to _______________________________.
A) reject H0;advertising is significant
B) not reject H0;advertising is significant
C) reject H0;advertising is not significant
D) not reject H0;advertising is not significant

A) reject H0;advertising is significant
B) not reject H0;advertising is significant
C) reject H0;advertising is not significant
D) not reject H0;advertising is not significant
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51
A marketing analyst wants to examine the relationship between sales (in $1,000s)and advertising (in $100s)for firms in the food and beverage industry and so collects monthly data for 25 firms.He estimates the model: Sales = β0 + β1 Advertising + ε.The following table shows a portion of the regression results.
When testing whether the slope coefficient differs from 3,the value of the test statistic is ____.
A) t23 = -1.895
B) t23 = -0.079
C) t23 = 0.079
D) t23 = 1.895

A) t23 = -1.895
B) t23 = -0.079
C) t23 = 0.079
D) t23 = 1.895
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52
A sports analyst wants to exam the factors that may influence a tennis player's chances of winning.Over four tournaments,he collects data on 30 tennis players and estimates the following model: Win = β0 + β1 Double Faults + β2Aces + ε,where Win is the proportion of winning,Double Faults is the percentage of double faults made,and Aces is the number of aces.A portion of the regression results are shown in the accompanying table.
Excel shows that the 95% confidence interval for β1 is [−0.12,−0.002].When determining whether or not Double Faults is significant at the 5% significance level,he ________________________________________________________.
A) rejects H0: β1 = 0,and concludes that Double Faults is significant
B) does not reject H0: β1 = 0,and concludes that Double Faults is significant
C) rejects H0: β1 = 0,and concludes that Double Faults is not significant
D) does not reject H0:β1 = 0,and concludes that Double Faults is not significant
![<strong>A sports analyst wants to exam the factors that may influence a tennis player's chances of winning.Over four tournaments,he collects data on 30 tennis players and estimates the following model: Win = β<sub>0</sub> + β<sub>1</sub> Double Faults + β<sub>2</sub>Aces + ε,where Win is the proportion of winning,Double Faults is the percentage of double faults made,and Aces is the number of aces.A portion of the regression results are shown in the accompanying table. Excel shows that the 95% confidence interval for β<sub>1</sub> is [−0.12,−0.002].When determining whether or not Double Faults is significant at the 5% significance level,he ________________________________________________________.</strong> A) rejects H<sub>0</sub>: β<sub>1</sub> = 0,and concludes that Double Faults is significant B) does not reject H<sub>0</sub>: β<sub>1</sub> = 0,and concludes that Double Faults is significant C) rejects H<sub>0</sub>: β<sub>1</sub> = 0,and concludes that Double Faults is not significant D) does not reject H<sub>0</sub>:β<sub>1</sub> = 0,and concludes that Double Faults is not significant](https://storage.examlex.com/TB4266/11eab0ce_30a0_3a2d_a083_0755bb61b7b5_TB4266_00.jpg)
A) rejects H0: β1 = 0,and concludes that Double Faults is significant
B) does not reject H0: β1 = 0,and concludes that Double Faults is significant
C) rejects H0: β1 = 0,and concludes that Double Faults is not significant
D) does not reject H0:β1 = 0,and concludes that Double Faults is not significant
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53
If the variance of the error term is not the same for all observations,we ___________________________.
A) get estimators that are biased
B) can perform tests of significance
C) cannot conduct tests of significance
D) Both get estimators that are biased and cannot conduct tests of significance are correct.
A) get estimators that are biased
B) can perform tests of significance
C) cannot conduct tests of significance
D) Both get estimators that are biased and cannot conduct tests of significance are correct.
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54
In regression,multicollinearity is considered problematic when two or more explanatory variables are ___________.
A) not correlated
B) rarely correlated
C) highly correlated
D) moderately correlated
A) not correlated
B) rarely correlated
C) highly correlated
D) moderately correlated
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55
Serial correlation is typically observed in __________________.
A) outliers
B) sparse data
C) time series data
D) cross-sectional data
A) outliers
B) sparse data
C) time series data
D) cross-sectional data
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56
A marketing analyst wants to examine the relationship between sales (in $1,000s)and advertising (in $100s)for firms in the food and beverage industry and so collects monthly data for 25 firms.He estimates the model: Sales = β0 + β1 Advertising + ε.The following table shows a portion of the regression results.
When testing whether the slope coefficient differs from 3,the critical values at the 5% significance level are −2.069 and 2.069.The conclusion to the test is to _______________________________________________.
A) reject H0;the slope coefficient differs from 3
B) not reject H0;the slope coefficient differs from 3
C) reject H0;the slope coefficient does not differ from 3
D) not reject H0;the slope coefficient does not differ from 3

A) reject H0;the slope coefficient differs from 3
B) not reject H0;the slope coefficient differs from 3
C) reject H0;the slope coefficient does not differ from 3
D) not reject H0;the slope coefficient does not differ from 3
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57
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
When testing whether Temperature is significant at the 5% significance level,she ________________________________________________________________.
A) rejects H0: β2 = 0,and concludes that Temperature is significant
B) does not reject H0: β2 = 0,and concludes that Temperature is significant
C) rejects H0:β2 = 0,and concludes that Temperature is not significant
D) does not reject H0:β2 = 0,and concludes that Temperature is not significant

A) rejects H0: β2 = 0,and concludes that Temperature is significant
B) does not reject H0: β2 = 0,and concludes that Temperature is significant
C) rejects H0:β2 = 0,and concludes that Temperature is not significant
D) does not reject H0:β2 = 0,and concludes that Temperature is not significant
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58
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
When testing whether Price is significant in explaining Attendance,the value of the test statistic is _____.
A) −4.085.
B) −1.201.
C) 1.201.
D) 4.085.

A) −4.085.
B) −1.201.
C) 1.201.
D) 4.085.
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59
Serial correlation occurs when the error term is ______________________.
A) dispersed evenly
B) randomly distributed
C) correlated across observations
D) uncorrelated across observations
A) dispersed evenly
B) randomly distributed
C) correlated across observations
D) uncorrelated across observations
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60
A marketing analyst wants to examine the relationship between sales (in $1,000s)and advertising (in $100s)for firms in the food and beverage industry and so collects monthly data for 25 firms.He estimates the model: Sales = β0 + β1 Advertising + ε.The following table shows a portion of the regression results.
Which of the following are the competing hypotheses used to test whether Advertising is significant in predicting Sales?
A) H0:b1 = 0;HA:b1 ≠ 0.
B) H0:b1 = 2.88;HA:b1 ≠ 2.88.
C) H0:β1 = 0;HA:β1 ≠ 0.
D) H0:β1 = 0;HA:β1 ≠ 0.

A) H0:b1 = 0;HA:b1 ≠ 0.
B) H0:b1 = 2.88;HA:b1 ≠ 2.88.
C) H0:β1 = 0;HA:β1 ≠ 0.
D) H0:β1 = 0;HA:β1 ≠ 0.
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61
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
When testing whether the explanatory variables Temperature and Rides are jointly significant,the error sum of squares for the restricted model is SSER = 12,343.78.Which of the following is the value of the test statistic when conducting this test?
A) −4.09
B) 25.33
C) 49.58
D) 99.78

A) −4.09
B) 25.33
C) 49.58
D) 99.78
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62
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
When testing whether the explanatory variables Temperature and Rides are jointly significant,the p-value associated with the test is 0.0000.At the 1% significance level,the researcher ________________________________________________________________________________.
A) rejects H0,and concludes that at least one of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
B) does not reject H0,and concludes that at least one of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
C) rejects H0,and concludes that neither of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
D) does not reject H0,and concludes that neither of the explanatory variables,Temperature and Rides,is significant in explaining Attendance

A) rejects H0,and concludes that at least one of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
B) does not reject H0,and concludes that at least one of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
C) rejects H0,and concludes that neither of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
D) does not reject H0,and concludes that neither of the explanatory variables,Temperature and Rides,is significant in explaining Attendance
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63
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2 + β3x3 + ε.
When testing whether the explanatory variables are jointly significant at the 5% significance level,the conclusion is to ____________________________________________________________________.
A) reject H0,and conclude that the explanatory variables are jointly significant
B) not reject H0,and conclude that the explanatory variables are jointly significant
C) reject H0,and conclude that the explanatory variables are not jointly significant
D) not reject H0,and conclude that the explanatory variables are not jointly significant

A) reject H0,and conclude that the explanatory variables are jointly significant
B) not reject H0,and conclude that the explanatory variables are jointly significant
C) reject H0,and conclude that the explanatory variables are not jointly significant
D) not reject H0,and conclude that the explanatory variables are not jointly significant
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64
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the capital asset pricing model (CAPM)model for Tiffany's return.
You would like to determine whether an investment in Tiffany's is riskier than the market.When conducting this test,you set up the following competing hypotheses: __________________.
A) H0:α = 0;HA:α ≠ 0
B) H0:β = 0;HA:β ≠ 0
C) H0:α ≤ 1;HA:α >0
D) H0:β ≤ 1;HA:β >1

A) H0:α = 0;HA:α ≠ 0
B) H0:β = 0;HA:β ≠ 0
C) H0:α ≤ 1;HA:α >0
D) H0:β ≤ 1;HA:β >1
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65
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
When testing whether Rides is significant at the 1% significance level,she ____________________________________________________________.
A) rejects H0:β3 = 0,and concludes that Rides is significant
B) does not reject H0:β3 = 0,and concludes that Rides is significant
C) rejects H0:β3 = 0,and concludes that Rides is not significant
D) does not reject H0:β3 = 0,and concludes that Rides is not significant

A) rejects H0:β3 = 0,and concludes that Rides is significant
B) does not reject H0:β3 = 0,and concludes that Rides is significant
C) rejects H0:β3 = 0,and concludes that Rides is not significant
D) does not reject H0:β3 = 0,and concludes that Rides is not significant
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66
A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β0 + β1 Price + β2 Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table.
According to the modified model,which of the following is a 95% prediction interval for Attendance when Price and Rides equal $85 and 30,respectively? (Note that t0.025,27 = 2.052. )
A) [12,740,56,080]
B) [16,330,53,450]
C) [26,080,42,740]
D) [28,900,41,500]
![<strong>A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β<sub>0</sub> + β<sub>1</sub> Price + β<sub>2</sub> Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table. According to the modified model,which of the following is a 95% prediction interval for Attendance when Price and Rides equal $85 and 30,respectively? (Note that t<sub>0.025,27</sub> = 2.052. )</strong> A) [12,740,56,080] B) [16,330,53,450] C) [26,080,42,740] D) [28,900,41,500]](https://storage.examlex.com/TB4266/11eab0ce_30a2_d249_a083_b54309be3886_TB4266_00.jpg)
![<strong>A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β<sub>0</sub> + β<sub>1</sub> Price + β<sub>2</sub> Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table. According to the modified model,which of the following is a 95% prediction interval for Attendance when Price and Rides equal $85 and 30,respectively? (Note that t<sub>0.025,27</sub> = 2.052. )</strong> A) [12,740,56,080] B) [16,330,53,450] C) [26,080,42,740] D) [28,900,41,500]](https://storage.examlex.com/TB4266/11eab0ce_30a2_d24a_a083_c7e71d974b8d_TB4266_00.jpg)
A) [12,740,56,080]
B) [16,330,53,450]
C) [26,080,42,740]
D) [28,900,41,500]
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67
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2 + β3x3 + ε.
When testing whether or not x1 and x2 have the same influence on y,the null hypothesis is ____________.
A) H0: β1 = β2
B) H0: β1 ≠ β2
C) H0: β1 + β2 = β3
D) H0: β1 + β2 = 0

A) H0: β1 = β2
B) H0: β1 ≠ β2
C) H0: β1 + β2 = β3
D) H0: β1 + β2 = 0
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68
A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β0 + β1 Price + β2 Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as
Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table.
According to the modified model,which of the following is a 95% confidence interval for expected Attendance when Price andRides equal $85 and 30,respectively? (Note that t0,025,27 = 2.052. )
A) [12,740,56,780]
B) [16,330,53,450]
C) [26,080,42,740]
D) [28,900,41,500]
Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table.
![<strong>A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β<sub>0</sub> + β<sub>1</sub> Price + β<sub>2</sub> Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table. According to the modified model,which of the following is a 95% confidence interval for expected Attendance when Price andRides equal $85 and 30,respectively? (Note that t<sub>0,025,27</sub> = 2.052. )</strong> A) [12,740,56,780] B) [16,330,53,450] C) [26,080,42,740] D) [28,900,41,500]](https://storage.examlex.com/TB4266/11eab0ce_30a2_8428_a083_ed40637c994f_TB4266_00.jpg)
A) [12,740,56,780]
B) [16,330,53,450]
C) [26,080,42,740]
D) [28,900,41,500]
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69
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the CAPM model for Tiffany's return.
When testing whether there are abnormal returns,the conclusion to the test is at the 5% significance level is to ___________________________________________________.
A) reject H0,and conclude there are abnormal returns
B) not reject H0,and conclude there are abnormal returns
C) reject H0,and do not conclude there are abnormal returns
D) not reject H0,and do not conclude there are abnormal returns

A) reject H0,and conclude there are abnormal returns
B) not reject H0,and conclude there are abnormal returns
C) reject H0,and do not conclude there are abnormal returns
D) not reject H0,and do not conclude there are abnormal returns
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70
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2 + β3x3 + ε.
At the 5% significance level,which of the following explanatory variable(s)is(are)individually significant?
A) Only x1
B) Only x3
C) x1 and x2
D) x2 and x3

A) Only x1
B) Only x3
C) x1 and x2
D) x2 and x3
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71
A manager at a local bank analyzed the relationship between monthly salary (y,in $)and length of service (x,measured in months)for 30 employees.She estimates the following model: Salary = β0 + β1 Service + ε.The following table summarizes a portion of the regression results.
Which of the following hypotheses will determine whether the intercept differs from zero?
A) H0:β0 = 0;HA:β0 ≠ 0
B) H0:β1 = 0;HA:β1 ≠ 0
C) H0:b0 = 0;HA:b0 ≠ 0
D) H0:b1 = 0;HA:b1 ≠ 0

A) H0:β0 = 0;HA:β0 ≠ 0
B) H0:β1 = 0;HA:β1 ≠ 0
C) H0:b0 = 0;HA:b0 ≠ 0
D) H0:b1 = 0;HA:b1 ≠ 0
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72
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the CAPM model for Tiffany's return.
When testing whether the beta coefficient is significantly greater than one,the relevant critical value at the 5% significance level is t0.05,58 = 1.672.The conclusion to the test is to _______________________________________________________________________________.
A) reject H0,and conclude that the return on Tiffany stock is riskier than the return on the market
B) not reject H0,and conclude that the return on Tiffany stock is riskier than the return on the market
C) reject H0,and conclude that the return on Tiffany stock is less risky than the return on the market
D) not reject H0,and conclude that the return on Tiffany stock is less risky than the return on the market

A) reject H0,and conclude that the return on Tiffany stock is riskier than the return on the market
B) not reject H0,and conclude that the return on Tiffany stock is riskier than the return on the market
C) reject H0,and conclude that the return on Tiffany stock is less risky than the return on the market
D) not reject H0,and conclude that the return on Tiffany stock is less risky than the return on the market
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73
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the CAPM model for Tiffany's return.
When testing whether the beta coefficient is significantly greater than one,the value of the test statistic is ____.
A) −1.98
B) 1.98
C) 4.33
D) 9.58

A) −1.98
B) 1.98
C) 4.33
D) 9.58
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74
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2 + β3x3 + ε.
When testing whether or not x1 and x2 are jointly significant,the null hypothesis is ____________.
A) H0:β1 = β2
B) H0:β1 ≠ β2
C) H0:β1 + β2 = 0
D) H0:β1 = β2 = 0

A) H0:β1 = β2
B) H0:β1 ≠ β2
C) H0:β1 + β2 = 0
D) H0:β1 = β2 = 0
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75
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the CAPM model for Tiffany's return.
When testing whether there are abnormal returns,or whether the alpha coefficient is significantly different from zero,the value of the test statistic is ____.
A) −1.98
B) 1.98
C) 4.33
D) 9.58

A) −1.98
B) 1.98
C) 4.33
D) 9.58
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76
A researcher analyzes the factors that may influence amusement park attendance and estimates the following model: Attendance = β0 + β1 Price + β2 Rides + ε,where Attendance is the daily attendance (in 1,000s),Price is the gate price (in $),and Rides is the number of rides at the amusement park.The researcher would like to construct interval estimates for Attendance when Price and Rides equal $85 and 30,respectively.The researcher estimates a modified model where Attendance is the response variable and the explanatory variables are now defined as Price* = Price - 85 and Rides* = Rides - 30.A portion of the regression results is shown in the accompanying table.
According to the modified model,which of the following is the predicted value for Attendance when Price and Rides equal $85 and 30,respectively?
A) 25,670
B) 34,410
C) 40,910
D) 55,600

A) 25,670
B) 34,410
C) 40,910
D) 55,600
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77
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
Which of the following are the hypotheses to test if the explanatory variables Temperature and Rides are jointly significant in explaining Attendance?
A) H0:β2 = β3 = 0;HA: At least one of the coefficients is nonzero.
B) H0:β2 = β3 = 0;HA: At least one of the coefficients is zero.
C) H0:β0 = β1 = 0;HA: At least one of the coefficients is nonzero.
D) H0:β0 = β1 = 0;HA: At least one of the coefficients is zero.

A) H0:β2 = β3 = 0;HA: At least one of the coefficients is nonzero.
B) H0:β2 = β3 = 0;HA: At least one of the coefficients is zero.
C) H0:β0 = β1 = 0;HA: At least one of the coefficients is nonzero.
D) H0:β0 = β1 = 0;HA: At least one of the coefficients is zero.
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78
A researcher analyzes the factors that may influence amusement park attendance.She estimates the following model: Attendance = β0 + β1 Price + β2 Temperature + β3 Rides + ε,whereAttendance is the daily attendance (in 1,000s),Price is the gate price (in $),Temperature is the average daily temperature (in oF),and Rides is the number of rides at the amusement park.A portion of the regression results is shown in the accompanying table.
Which of the following is the value of the test statistic for testing the joint significance of the linear regression model?
A) −4.09
B) 0.04
C) 9.95
D) 99.78

A) −4.09
B) 0.04
C) 9.95
D) 99.78
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79
Tiffany & Co.has been the world's premier jeweler since 1837.The performance of Tiffany's stock is likely to be strongly influenced by the economy.Monthly data for Tiffany's risk-adjusted return and the risk-adjusted market return are collected for a five-year period (n = 60).The accompanying table shows the regression results when estimating the CAPM model for Tiffany's return.
To determine whether abnormal returns exist,which of the following competing hypotheses do you set up?
A) H0:α = 0;HA:α ≠ 0
B) H0:β = 0;HA:β ≠ 0
C) H0:α ≤ 1;HA:α > 1
D) H0:β ≤ 1;HA:β > 1

A) H0:α = 0;HA:α ≠ 0
B) H0:β = 0;HA:β ≠ 0
C) H0:α ≤ 1;HA:α > 1
D) H0:β ≤ 1;HA:β > 1
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80
A manager at a local bank analyzed the relationship between monthly salary (y,in $)and length of service (x,measured in months)for 30 employees.She estimates the following model: Salary = β0 + β1 Service + ε.The following table summarizes a portion of the regression results.
Which of the hypotheses will determine whether the slope differs from zero?
A) H0:β0 = 0;HA: β0 ≠ 0
B) H0:β1 = 0;HA: β1 ≠ 0
C) H0:b0 = 0;HA: b0 ≠ 0
D) H0:b1 = 0;HA: b1 ≠ 0

A) H0:β0 = 0;HA: β0 ≠ 0
B) H0:β1 = 0;HA: β1 ≠ 0
C) H0:b0 = 0;HA: b0 ≠ 0
D) H0:b1 = 0;HA: b1 ≠ 0
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