2
Business Stats Exam 4 Review questions with accurate || || || || || || || ||
detailed solutions ||
Excel and virtually all other statistical packages report the p-value ________. - ✔✔for a two-
|| || || || || || || || || || || || || ||
tailed test that assesses whether the regression coefficient differs from zero
|| || || || || || || || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x + ε.
|| || || || || || || || || || || || || || ||
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 0.083 3.56 0.02 0.9822 || || || ||
X 1.417 0.63 2.25 0.0745
|| || || ||
Is x significantly related to y at the 5% significance level? - ✔✔No, because the p-value of
|| || || || || || || || || || || || || || || || ||
0.0745 is greater than 0.05.
|| || || ||
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.
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 40.10 14.08 2.848 0.0052 || || || ||
Advertising 2.88 1.52 -1.895 0.0608 || || || ||
,2
Which of the following are the competing hypotheses used to test whether Advertising is
|| || || || || || || || || || || || || ||
significant in predicting Sales? - ✔✔H0:β1 = 0; HA:β1 ≠ 0.
|| || || || || || || || || ||
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.
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 40.10 14.08 2.848 0.0052 || || || ||
Advertising 2.88 1.52 -1.895 0.0608 || || || ||
When testing whether Advertising is significant at the 10% significance level, the conclusion
|| || || || || || || || || || || || ||
is to ________. - ✔✔reject H0; we can conclude advertising is significant
|| || || || || || || || || || ||
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 + β2 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.
|| || || || || || || || ||
Df ss ms f significance f
|| || || || ||
Regression 2 1.24 .620 41.85 5.34E-09 || || || || ||
Residual 27 0.40 .015 || || ||
Total 29 1.64 || ||
Coefficients Standard Error T-Stat P-Value Lower 95 Upper 95 || || || || || || || ||
Intercept .451 .080 5.646 5.4E-06 .287 .614|| || || || || ||
, 2
Double -.007 .0024 -2.875 .0078 -.012 -.002
|| || || || || ||
Aces .015 .003 4.65 7.8E-05 .008 .023
|| || || || || ||
When testing whether the explanatory variables jointly influence the response variable, the
|| || || || || || || || || || || ||
null hypothesis is ________. - ✔✔H0:β1 = β2 = 0
|| || || || || || || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2
|| || || || || || || || || || || || || || ||
+ β3x3 + ε.
|| || || ||
Df ss ms f significance f
|| || || || ||
Regression 3 453 151 5.03 .0030 || || || || ||
Residual 85 2,521 30 || || ||
Total 88 2,974 || ||
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 14.96 3.08 4.86 0 || || || ||
X1 .04 .34 .12 .9066
|| || || ||
X2 .87 .29 3 .0035
|| || || ||
X3 .46 .22 2.09 .0400
|| || || ||
When testing whether the explanatory variables are jointly significant at the 5% significance
|| || || || || || || || || || || || ||
level, the conclusion is to ________. - ✔✔reject H0, and conclude that the explanatory
|| || || || || || || || || || || || || ||
variables are jointly significant || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2
|| || || || || || || || || || || || || || ||
+ β3x3 + ε.
|| || || ||
Df ss ms f significance f
|| || || || ||
Regression 3 453 151 5.03 .0030 || || || || ||
Residual 85 2,521 30 || || ||
Business Stats Exam 4 Review questions with accurate || || || || || || || ||
detailed solutions ||
Excel and virtually all other statistical packages report the p-value ________. - ✔✔for a two-
|| || || || || || || || || || || || || ||
tailed test that assesses whether the regression coefficient differs from zero
|| || || || || || || || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x + ε.
|| || || || || || || || || || || || || || ||
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 0.083 3.56 0.02 0.9822 || || || ||
X 1.417 0.63 2.25 0.0745
|| || || ||
Is x significantly related to y at the 5% significance level? - ✔✔No, because the p-value of
|| || || || || || || || || || || || || || || || ||
0.0745 is greater than 0.05.
|| || || ||
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.
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 40.10 14.08 2.848 0.0052 || || || ||
Advertising 2.88 1.52 -1.895 0.0608 || || || ||
,2
Which of the following are the competing hypotheses used to test whether Advertising is
|| || || || || || || || || || || || || ||
significant in predicting Sales? - ✔✔H0:β1 = 0; HA:β1 ≠ 0.
|| || || || || || || || || ||
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.
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 40.10 14.08 2.848 0.0052 || || || ||
Advertising 2.88 1.52 -1.895 0.0608 || || || ||
When testing whether Advertising is significant at the 10% significance level, the conclusion
|| || || || || || || || || || || || ||
is to ________. - ✔✔reject H0; we can conclude advertising is significant
|| || || || || || || || || || ||
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 + β2 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.
|| || || || || || || || ||
Df ss ms f significance f
|| || || || ||
Regression 2 1.24 .620 41.85 5.34E-09 || || || || ||
Residual 27 0.40 .015 || || ||
Total 29 1.64 || ||
Coefficients Standard Error T-Stat P-Value Lower 95 Upper 95 || || || || || || || ||
Intercept .451 .080 5.646 5.4E-06 .287 .614|| || || || || ||
, 2
Double -.007 .0024 -2.875 .0078 -.012 -.002
|| || || || || ||
Aces .015 .003 4.65 7.8E-05 .008 .023
|| || || || || ||
When testing whether the explanatory variables jointly influence the response variable, the
|| || || || || || || || || || || ||
null hypothesis is ________. - ✔✔H0:β1 = β2 = 0
|| || || || || || || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2
|| || || || || || || || || || || || || || ||
+ β3x3 + ε.
|| || || ||
Df ss ms f significance f
|| || || || ||
Regression 3 453 151 5.03 .0030 || || || || ||
Residual 85 2,521 30 || || ||
Total 88 2,974 || ||
Coefficients Standard Error T-Stat P-Value || || || ||
Intercept 14.96 3.08 4.86 0 || || || ||
X1 .04 .34 .12 .9066
|| || || ||
X2 .87 .29 3 .0035
|| || || ||
X3 .46 .22 2.09 .0400
|| || || ||
When testing whether the explanatory variables are jointly significant at the 5% significance
|| || || || || || || || || || || || ||
level, the conclusion is to ________. - ✔✔reject H0, and conclude that the explanatory
|| || || || || || || || || || || || || ||
variables are jointly significant || || ||
The accompanying table shows the regression results when estimating y = β0 + β1x1 + β2x2
|| || || || || || || || || || || || || || ||
+ β3x3 + ε.
|| || || ||
Df ss ms f significance f
|| || || || ||
Regression 3 453 151 5.03 .0030 || || || || ||
Residual 85 2,521 30 || || ||
