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Unformatted text preview: = 1 + 1X . The time is in minutes and the strength is measured in pounds per square inch, MSE = 0.5,
= 30,
= 104.
Determine the 95% confidence interval for the mean value of metal strength when the average
heating time is 4 minutes.
A. (4.721 5.279)
B. (4.523 5.477)
C. (3.325 4.675)
D. (4.325 5.675) 92. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. Partial results based on a sample of 10 metal sheets are given below. The
simple linear regression equation is = 1 + 1X . The time is in minutes and the strength is measured in pounds per square inch, MSE = 0.5,
= 30,
= 104.
Determine the 95% prediction interval for the strength of a metal sheet when the average
heating time is 4 minutes. The distance value has been found to be equal to 0.17143.
A. (3.235 6.765)
B. (3.370 6.629)
C. (3.155 6.845)
D. (2.235 5.765) 11170 Chapter 01  An Introduction to Business Statistics 93. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. Partial results based on a sample of 10 metal sheets are given below. The
simple linear regression equation is = 1 + 1X . The time is in minutes and the strength is measured in pounds per square inch, MSE = 0.5,
= 30,
= 104.
Determine the 95% prediction interval for the strength of a metal sheet when the average
heating time is 2.5 minutes.
A. (1.68 5.32)
B. (2.94 4.06)
C. (1.78 5.22)
D. (0.78 4.22) 94. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. Partial results based on a sample of 10 metal sheets are given below. The
simple linear regression equation is = 1 + 1X . The time is in minutes and the strength is measured in pounds per square inch, MSE = 0.5,
= 30,
= 104.
Determine the 95% confidence interval for the average strength of a metal sheet when the
average heating time is 2.5 minutes.
A. (2.94 4.06)
B. (1.78 5.22)
C. (3.31 3.69)
D. (1.94 3.06) 95. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. 95% prediction interval for the strength of a metal sheet when the average
heating time is 4 minutes is from 3.235 to 6.765. We are 95% confident that an individual
sheet of metal heated for four minutes will have strength of at least 4 pounds per square inch.
Do you agree with this statement?
A. Yes, agree
B. No, disagree 11171 Chapter 01  An Introduction to Business Statistics 96. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. 95% confidence interval for the average strength of a metal sheet when the
average heating time is 4 minutes is from 4.325 to 5.675. Therefore, we are confident at α = .
05 that the average strength of metal heated for four minutes is between 4.325 and 5.675
pounds per square inch. Do you agree or disagree with this statement?
A. Agree
B. Disagree 97. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. The simple linear regression equation is
= 1 + 1X and sample coefficient
of determination (r2) = .7777. The time is in minutes and the strength is measured in pounds
per square inch. Test to determine if there is a significant correlation between the heating time
and strength of the metal.
Using H0: ρ = 0 vs. HA: ρ ≠ 0 at α = .05, determine the test statistic and decision.
A. t = 1.65, fail to reject the null hypothesis
B. t = 2.306, reject the null hypothesis
C. t = 5.292, reject the null hypothesis
D. t = 8.00, reject the null hypothesis 98. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. The sample size consists of ten metal sheets. Residuals are calculated for all
ten metal sheets and ordered from smallest to largest.
Determine the normal point for the smallest residual.
A. .0645
B. 1.52
C. 1.30
D. 1.28 11172 Chapter 01  An Introduction to Business Statistics 99. An experiment was performed on a certain metal to determine if the strength is a function
of heating time. The sample size consists of ten metal sheets. Residuals are calculated for all
ten metal sheets and ordered from smallest to largest.
Determine the normal point for the second largest residual (ninth residual in the ordered
array).
A. 0.99
B. 1.28
C. 0.84
D. 0.90 100. A local tire dealer wants to predict the number of tires sold each month. He believes that
the number of tires sold is a linear function of the amount of money invested in advertising.
He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and
advertising expenditures (in thousands of dollars). Based on the data set with 6 observations,
the simple linear regression model yielded the following results.
= 24
= 124
= 42
= 338
= 196
Determine the values of SSE and SST
A. 28, 44
B. 24, 42
C. 16, 44
D. 16, 28 11173 Chapter 01  An Introduction to Business Statistics 101. A local tire dealer wants to pr...
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