A pooled proportion estimate may be used to calculate the test statistic for a test of the equality of proportions when the

A. sample sizes are small.

B. samples are independently drawn from the populations.

C. null hypothesis states that the two population proportions are equal.

D. populations are normally distributed.

When testing for differences between two means, the Behrens-Fisher problem arises when the sample populations are A. are normal with unequal variances. B. normal with equal variances. C. are non-normal and have equal variances. D. are non-normal and have unequal variances.

If we simultaneously examine the effects of two factors on the dependent variable, along with the effects of interactions between different levels of those factors, we are performing a three-factor analysis of variance. A. True B. False

The purpose of designing a randomized block experiment is to reduce the between-treatments variation (SST) to more easily detect differences between the treatment means. A. True B. False

In two-factor ANOVA, the MSE must always be positive, but MSA or MSB may be negative. A. True B. False

Two independent samples of 20 each from male and female students of a large university have been selected at random. To test for difference in the grade point average between male and female students, the most likely ANOVA to fit this test situation is the A. two-factor ANOVA. B. completely randomized design of the analysis of variance C. randomized block design. D. chi-square test .

Which of the following statistics from the ANOVA table do not have an additive relationship? A. Degrees of freedom B. Sum of squares C. Mean squares D. It is not possible to tell.

Which of the following is not required to perform a one-factor ANOVA? A. The populations must be normally distributed. B. The sample sizes must be equal. C. The population variances must be equal. D. The samples for each treatment must be selected randomly and independently.

The appropriate measure of central location of ordinal data is the A. mean. B. median. C. mode. D. all of these.

The nonparametric counterpart of the parametric one-way analysis of variance F-test is the A. Friedman test. B. Kruskal-Wallis test. C. Spearman’s rho. D. Wilcoxon signed rank sum test.

Consider the following data set: 14, 14, 15, 16, 18, 19, 19, 20, 21, 22, 23, 25, 25, 25, 25, and 28. The rank assigned to the four observations of value 25 is A. 12.5 B. 12 C. 13 D. 13.5

Of the values for a chi-squared test statistic listed below, which one is most likely to lead to rejecting the null hypothesis in a goodness-of-fit test? A. 2.1 B. 45 C. 1.2 D. 0

A test of independence in a contingency table with five rows and four columns has the following degrees of freedom: A. 12 B. 20 C. 9 D. 7

If each group has at least five observations, the distribution of the Kruskal-Wallis H is A. t B. F C. x2 D. z

The distribution for Spearman’s rho is A. t B. z C. x2. D. F

The Kruskal-Wallis test statistic may be approximated by a chi-squared distribution with c-1 degrees of freedom, where c is the number of populations, whenever the sample sizes are all greater than or equal to A. 15 B. 30 C. 25 D. 5

In regression analysis, if the coefficient of determination is 1.0, then the coefficient of correlation must be 1.0. A. True B. False

From the coefficient of multiple determination, we cannot detect the strength of the relationship between the dependent variable y and any individual independent variable. A. True B. False

The bivariate correlation coefficient always has the same sign as b1 in Y = b0 + b1X. A. True B. False

What randomness exists in the linear regression model? A. The randomness from the explanatory variables, the X’s B. The randomness from what is unexplained, the error C. The randomness of the dependent variable, the Y’s D. None of these

The regression line y = 2 + 3x has been fitted to the data points (4,11), (2,7), and (1,5). The sum of squares for error will be 10.0 A. True B. False

Given that SSE = 84 and SSR = 358.12, the coefficient of correlation, also called the Pearson coefficient of correlation, must be 0.90. A. True B. False

An inverse relationship between an independent variable x and a dependent variable y means that, as x increases, y decreases, and vice versa. A. True B. False

Which of the following statements regarding multicollinearity is not true? A. It does not affect the F-test of the analysis of variance. B. It is also called collinearity and

intercorrelation. C. It exists in virtually all multiple regression models. D. It is a condition that exists when independent variables are highly correlated with dependent variable.

If a group of independent variables are not significant individually but are significant as a group at a specified level of significance, this is most likely due to A. multicollinearity. B. the presence of binary variables. C. the absence of binary variables. D. autocorrelation

If the Durbin-Watson statistic, DW, has values greater than 2, this indicates A. a positive first–order autocorrelation. B. a negative first–order autocorrelation. C. no first–order autocorrelation at all. D. None of the above

The time series component that reflects variability over short, repetitive time periods that last less than one year is called A. cyclical variation. B. irregular variation. C. seasonal variation. D. long–term trend.

A time series is A. a set of measurements on a variable taken over some time period in chronological order. B. a model that attempts to analyze the relationship between a dependent variable and one or more independent variables. C. a model that attempts to forecast the future value of a variable. D. a set of measurements on a variable collected at the same time or approximately the same period of time.

If we want to measure the seasonal variations on stock market performance by quarter, we would need A. 3 indicator variables. B. 2 indicator variables. C. 1 indicator variables.

D. 4 indicator variables.

Variations in output that are caused by specific temporary events such as machine malfunction are A. special causes. B. common causes. C. out-of-control causes. D. All of the these

When the only sources of variation in a production process are caused by chance, the process is said to be A. out of control but in balance. B. under control. C. out of control. D. out of balance but under control.

When no point lies outside the control limits of a chart, we conclude that variation in the process is A. due to special causes and there is enough evidence to infer that the process is under control. B. due to common cause and there is enough evidence to infer that the process is out of control. C. due to common cause and there is enough evidence to infer that the process is out of control. D. due to special causes and there is not enough evidence to infer that the process is out of control.