BNAD 277 Ch 13

One-Way ANOVA analyzes the effect of one factor on the population mean. It is based on a: A. randomized block design B. completely randomized design C. factorial design D. balanced incomplete block design

B. completely randomized design

ANOVA is a statistical technique used to determine if differences exist between the means of two populations.

False

If units within each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a completely randomized design.

False

In general, blocks are the levels at which we hold an integral factor fixed, so that we can measure its contribution to the variation within the samples.

False

One-way ANOVA analyzes the effect of one factor on the population mean and it is based on a completely randomized design.

True

The interaction test is performed before making any conclusions based on the tests for the main effects.

True

We use ANOVA to test for differences between population means by examining the amount of variability between the samples relative to the amount of variability within the samples.

True

13. If there are five treatments under study, the number of pairwise comparisons is: A. 15 B. 5 C. 20 D. 10

10

Tukey's honestly significant differences (HSD) method ensures that the probability of a Type I error remains fixed irrespective of the number of: A. pairwise comparisons B. treatments C. replications within each treatment D. replications for each combination of factor A and factor

A. pairwise comparisons

Tukey's 100(1 - α)% confidence interval for the difference between two population means μi - μj for balanced data is given by .

B

Identify the assumption that is not applicable for a one-way ANOVA test. A. The populations are normally distributed B. The population standard deviations are not all equal C. The samples are selected independently D. The sample is drawn at random from each population

B.The population standard deviations are not all equal

Which of these null hypotheses is applicable for a two-way ANOVA test with interaction? A. There is interaction between factors A and B. B. Factor A and factor B means differ. C. There is no interaction between factors A and B. D. Factor A and factor B means do not differ.

C. There is no interaction between factors A and B.

If units with each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a: A. factorial design B. completely randomized design C. randomized block design D. balanced incomplete block design

C. randomized block design

Tukey's honestly significant differences (HSD) method uses Fishers least differences (LSD) method for pairwise comparisons. A. t values; studentized range values B. studentized range values; F values C. F values; t values D. studentized range values; t values instead of when compared to

D studentized range values; t values instead of when compared to

When the null hypothesis is rejected in an ANOVA test, Fisher's least significant difference method is superior to Tukey's honestly significant differences method to determine which population means differ.

False

If the amount of variability between treatments is significantly greater than the amount of variability within treatments, then: A. reject the null hypothesis of equal population means B. do not reject the null hypothesis of equal population means C.conclude that the ratio of between-treatments variability to within-treatments variability is significantly less than 1 D. perform further analysis using the two-way ANOVA with interaction

A. . reject the null hypothesis of equal population means

Fisher's 100(1 - α)% confidence interval for the difference between two population means μi - μj is: B.

B

Fisher's least difference (LSD) method is applied when the: A. ANOVA test has not rejected the null hypothesis of equal population means B. ANOVA test has rejected the null hypothesis of equal population means C. Two-sample t test is not applicable D. None of the above

B. ANOVA test has rejected the null hypothesis of equal population means

When using Fisher's least significant difference (LSD) method at some stated significance level, the probability of committing a Type I error increases as the number of: A. pairwise comparisons decreases B. pairwise comparisons increases C. sample size increases D. treatments decreases

B. pairwise comparisons increases

In a two-way ANOVA test, how many null hypotheses are tested? A. 1 B. 1 or 2 C. 2 or 3 D. More than 3

C. 2 or 3

Which of the following is the correct interpretation of the Fisher's 100(1 - α)% confidence interval for μi - μj? A.If the interval includes the value zero, the null hypothesis, that H0: μi - μj = 0, is rejected for at α level of significance B.If the interval does not include the value zero, the null hypothesis, that H0: μi - μj = 0, is rejected at 100(1 - α)% level of significance C.If the interval does not include the value zero, the null hypothesis, that H0: μi - μj = 0, is rejected at α level of significance D.If the interval includes the value zero, the null hypothesis, that H0: μi - μj = 0, is rejected at 100(1 - α)% level of significance

C. If the interval does not include the value zero, the null hypothesis, that H0: μi - μj = 0, is rejected at α level of significance

If the interaction between two factors is not significant, the next tests to be done are: A. None, the analysis is complete. B. None, gather more data. C. Tests about the population means of factor A or factor B using two-way ANOVA without interaction. D. Tukey's confidence intervals.

C. Tests about the population means of factor A or factor B using two-way ANOVA without interaction

The variability due to chance, also known as within-treatments variability, is the estimate of σ2 which is based on the: A. variability of the data across different samples B. consistency of the data within each sample C. variability of the data within each sample D. reliability of the data within each sample

C.variability of the data within each sample

When using Fisher's LSD method at some stated significance level α, the probability of committing a Type I error increases as the number of pairwise comparisons increases. True False

True

One of the disadvantages of Fisher's least difference (LSD) method is that the probability of committing a: A. Type II error increases as the number of pairwise comparisons increases. B. Type I error increases as the number of pairwise comparisons decreases. C. Type II error increases as the number of pairwise comparisons decreases. D. Type I error increases as the number of pairwise comparisons increases.

D. Type I error increases as the number of pairwise comparisons increases.

The between-treatments variability is the estimate of σ2 which is based on the variability due to chance.

False

When two factors interact, the effect of one factor on the population mean depends upon the specific value or level present for the other factor.

True

Between-treatments variability is based on a weighted sum of squared differences between the: A. population variances and the overall mean of the data set B. sample means and the overall mean of the data set C. sample variances and the overall mean of the data set D. population means and the overall mean of the data set

sample means and the overall mean of the data set