Exam 13: Testing for Significance in Multiple Groups: the Analysis of Variance Statistic

One of the assumptions of the Analysis of Variance test is homogeneity of variances.If the data violate this assumption they are referred to as:

How many groups can be used in the analysis of variance?

If data are not normally distributed,which of the two inferential tests below should not be used?

The ANOVA cannot be used for a 2-group comparison.

The best approach,of those listed below,to determining differences between individual groups is to use

If the group variances are unequal,you should use the unequal variance ANOVA test.

If an analysis of variance is significant,you should use a multiple comparison test to locate groups with significantly different comparisons.

A reasonable alternative to the ANOVA statistic is the

The analysis of variance is part of the nonlinear specific model,a family of statistical techniques.

If there are multiple violations of the assumptions of ANOVA,it doesn't really make a difference because ANOVA is very robust to these violations.

Multiple comparison tests compare only the highest and lowest group values.All others have to be estimated using.

The concept of "error" is expressed in the ANOVA by

A determination of which groups,if any,are significantly different from each other cannot be done with the analysis of variance test.

ANOVA can accommodate multiple dependent variables.

Which reason below best answers why a two-tailed hypothesis should be used with an analysis of variance.

If you are doing 20 two-at-a-time t-tests,you would expect 1 test result to be the result of error.

The effect of an independent variable in the ANOVA is found

An independent variable with 6 values (groups)can be used with a the t-test,but you would have to make several ?t-tests.Of the various problems below,which is the one reflected by making multiple t-tests?

The analysis of variance is designed for which level of measurement?

Only a one-tailed hypothesis should be used with the analysis of variance statistic.