Unformatted text preview: 95% confident that the mathematics test score is estimated to be at
least 61.69 and at most 68.55. This is based on the assumption that 50% of the teachers have a
mathematics degree, the average age is 43 and the average salary is $48,300.
t.025,32 = 2.036
Distance value = (1.68/7.6209)2 = 0.0486
65.12 ± 2.036 (7.6209) = 61.69 to 68.54 AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Confidence & prediction intervals 11445 Chapter 01  An Introduction to Business Statistics 122. A member of the state legislature has expressed concern about the differences in the
mathematics test scores of high school freshmen across the state. She asks her research
assistant to conduct a study to investigate what factors could account for the differences. The
research assistant looked at a random sample of school districts across the state and used the
factors of percentage of mathematics teachers in each district with a degree in mathematics,
the average age of mathematics teachers and the average salary of mathematics teachers s = 7.62090
Analysis of Variance Additional information related to this point estimate of 65.12 is given below.
Predicted Values for New Observations
50% with math degree, average age of 43 and average salary is 48.3
New Calculate the 95% prediction interval for this point estimate.
49.22 to 81.02
t.025,32 = 2.036
Distance value = (1.68/7.6209)2 = 0.0486
65.12 ± 2.036 (7.6209) = 49.22 to 81.02 AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Confidence & prediction intervals Chapter 15 11446 Chapter 01  An Introduction to Business Statistics Model Building and Model Diagnostics
True / False Questions 1. If we increase the number of independent variables in a multiple regression model, the F
statistic will always increase.
True False 2. When the quadratic regression model y =
shows the rate of curvature of the parabola.
True False 0 + x+ 1 x2 + ε is used the term 2 1 3. The variance inflation factor measures the relationship between the dependent variable and
the rest of the independent variables in the regression model.
True False 4. Even when an unimportant variable is added to a regression model, the explained variation
will increase.
True False
5. The standard error decreases if and only if the adjusted multiple coefficient of
determination decreases.
True False 6. One way to identify outliers with respect to their x values is to calculate their leverage
values.
True False 11447 Chapter 01  An Introduction to Business Statistics 7. Cook's distance is a way to determine whether an observation is influential.
True False 8. An independent variable dropped during an iteration of the backward elimination process
may be added back to the regression model during a later iteration of the process.
True False 9. In comparing regression models, the regression model with the largest R2 will also have the
smallest standard error(s).
True False 10. Multicollinearity hinders the regression model's ability to predict the dependent variable
on the basis of a combination of values of the independent variable in the experimental
region.
True False 11. In a multiple regression mode if the largest VIF is 21.6, then it can be concluded that there
are indications of multicollinearity.
True False 12. In multiple regression analysis, if the simple correlation coefficient between the dependent
variable and one of the independent variables is .95, then this indicates that the problem of
multicollinearity exists.
True False 13. When there are indications of autocorrelation, first an investigation should be conducted
to determine whether one or more independent variables that might explain the
autocorrelation have been omitted from the model.
True False 11448 Chapter 01  An Introduction to Business Statistics 14. If a particular multiple regression model has a small value of the C statistic and C for this
model is less than k + 1, where k is the number of independent variables in the model, then
the model should be considered biased and therefore undesirable.
True False Multiple Choice Questions 15. The general form of the quadratic multiple regression models is:
A. y = 1X1 + 2X2 +
B. y = 0 + 1X1 + 2X2 +
C. y = 0 + X+ D. y = 0 + E. y = 0 + 1 X2 + 1 1 2 X2 + X1 + X22 + 2 16. As we increase the number of independent variables in a multiple regression model, the F
statistic will _____ increase.
A. Always
B. Sometimes
C. Never 17. In the quadratic regression model
zero, then the parabola opens __________.
A. Less than, upward
B. Greater than, upward
C. Greater than, either upward or downward
D. Less than, either upward or downward
E. Equal to, downward if the term 11449 2 is ______ Chapter 01  An Introduction to Business Statistics 18. In the quadratic regression model
the:
A. Rate of curvature of the parabola.
B. Value of Y when X is zero.
C. Shift parameter of the parabola.
D. Yintercept of the parabola. the 19. In the quadratic regression model
the:
A. Rate of curvature of the parabola.
B. Value of Y when X is zero.
C. Shift parameter of the parabola.
D. Yintercept of the parabola. , the v2 term represents 2...
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 Winter '14

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