Exam 16: Analysis of Variance and

The most common use of the covariate is to remove extraneous variation from the dependent variable.

The Kruskal- Wallis one- way analysis of variance and the k- sample median test have the same null hypothesis -"medians of the k populations are equal."

Analysis of variance is so named because it examines the variability or variation in the sample (dependent variable) and, based on the variability, determines whether there is reason to believe that the population means differ.

If you are estimating y², you are at which step in the procedure for conducting one- way analysis of variance?

Contrasts are used in ANOVA to determine which of the means are statistically different.

In analysis of variance, it is assumed that all the groups have the same variation in the population.

How consumers' intentions to buy a brand vary with different levels of price and different levels of distribution is best analyzed via .

y² assumes a value of 0 when all the category means are equal, indicating that X has no effect of X on Y.

The strength of the effects of X (independent variable or factor) on Y (dependent variable) is measured by .

A test finding that some differences exist between some of the treatment groups is a test of the .

The strength of the joint effect of two (or more) factors or the overall effect is known as .

A statistical technique for examining the differences among means for two or more populations is called .

In determining how different price levels will affect a household's cereal consumption, it may be essential to take household size into account. This is best analyzed by .

The Kruskal- Wallis one- way analysis of variance also examines the difference in medians.

The n- way ANOVA assumes that the design was orthogonal, or balanced (the number of cases in each cell was the same).

Which step are you on in the procedure for conducting one- way analysis of variance if you are decomposing SSy into two components using the equation SSy = SS_between + SS_within?

The total variation in Y, denoted by SSy, can be decomposed into which two components?

In one- way ANOVA, separation of the variation observed in the dependent variable into the variation due to the independent variables plus the variation due to error is called _ .

A covariate is a independent variable used in .

SS_between is the portion of the sum of squares in Y related to the independent variable or factor X.