1. Another name for the residual term in a regression equation is
A. residual analysis.
B. random error.
D. pooled variances.
2. A chi-square test for independence with 8 degrees of freedom results in a test statistic of 18.21. Using
the chi-square table, the most accurate statement that can be made about the p-value for this test is that
A. p-value < 0.01.
B. 0.10 > p-value > 0.05.
C. 0.025 > p-value > 0.01.
D. 0.05 > p-value > 0.025.
3. A left-tail area in the chi-square distribution equals 0.95. For df = 10, the table value equals
4. A regression analysis between sales (in $1000) and advertising (in $) resulted in the following least
squares line: yˆ = 80,000 + 5x. This implies that an increase of _______ in advertising is expected to result
in an increase of _______ in sales.
A. $5, $5,000
B. $1, $5,000
C. $1, $5
D. $1, $80,005
5. With larger and larger numbers of categories in chi-square tests, the chi-square distribution takes on the
shape of the _______ distribution.
6.The F-statistic in a one-way ANOVA represents the variation
A. between the treatments divided by the variation within the treatments.
B. within the treatments divided by the variation between the treatments.
C. within the treatments minus the variation between the treatments.
D. between the treatments plus the variation within the treatments.
7. Which of the following statements are true regarding the simple linear regression model yi = β0 + β1xi +
A. yi is a value of the dependent variable (y) and xi is a value of the independent variable (x).
B. β1 is the y-intercept of the regression line.
C. β0 is the slope of the regression line.
D. εi is a nonrandom error.
8. Given the significance level 0.05, the F-value for the degrees of freedom, df = (3,7) is
9. In testing the difference between two population means using two independent samples, the sampling
distribution of the sample mean difference x̄1 − x̄2 is normal if the
A. population sizes are both greater than 30.
B. populations are normal.
C. populations are nonnormal and the sample sizes are large.
D. sizes are both greater than 30.
10. A “best-fit” mathematical equation for the values of two variables, x and y, is called
A. regression analysis.
B. errors of prediction.
C. scatter diagram.
D. correlation analysis.
11. A random sample of males and females involved in rear-end accidents results in the following Minitab
What is the value of the test statistic (Z score)?
N MEAN MEDIAN TRMEAN STDEV SEMEAN
FEMALES 33 23.91 20.00 23.38 9.77 1.70
MALES 38 28.87 28.50 28.44 9.67 1.57
12. An indication of no linear relationship between two variables would be a coefficient of
A. determination equal to −1.
B. determination equal to 1.
C. correlation of 0.
D. correlation equal to −1.
13. The object on which the response and factors are observed is called
B. experimental unit.
D. factor level.
14. Consider the following data values of variables x and y.
Find the least squares regression line.
x 4 2 6 4 3
y 5 3 7 6 5
A. −1.045 + 0.932x
B. 1.659 + 0.932x
C. 21.206 + 1.073x
D. 1.122 + 1.073x
15. What is the slope of the line that passes through the points (−5, −8) and (3,8)?
16. Given the significance level 0.025, the F-value for the degrees of freedom, df = (7,3) is
17. In testing a population variance or constructing a confidence interval for the population variance, an
essential assumption is that
A. the population is normally distributed.
End of exam
B. expected frequencies equal or exceed 5.
C. sample size exceeds 30.
D. the population is uniformly distributed.
18. In using the ANOVA models, the assumptions made about the data are
A. the samples are independent.
B. all 3 assumptions made here about the data.
C. the population variances are equal.
D. the population distributions are normal.
19. In a hypothesis test for the population variance, the alternate hypothesis is the population variance does
not equal 17.0. The significance level to be used is 0.05 and the sample size to be taken is 25. The table
value(s) to use from the chi-square distribution is/are
A. 12.401 and 39.364.
C. 13.120 and 40.647.
20. The vertical distances between observed and predicted values of y are called
A. errors of prediction.
B. methods of least squares.
C. least square lines.