Exam 16: Analysis of Variance and Covariance

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A test of the significance of the main effect for each individual factor is a test of the ________.

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Analysis of variance and analysis of covariance are tests of differences between two means or median.

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SSwithin is referred to as SSerror.

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A covariate is a ________ independent variable used in ________.

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The effects of X on Y is measured by ________.

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When using SPSS Windows one-way ANOVA can be efficiently performed using the ________ program.

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________ are contrasts made after the analysis.

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η2 assumes a value of 0 when all the category means are equal,indicating that X has no effect of X on Y.

(True/False)
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________ are determined before conducting the analysis,based on the researcher's theoretical framework.

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Which statement is not true concerning interactions resulting from ANOVA?

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Analysis of covariance is most useful when the covariate is not linearly related to the dependent variable and is not related to the factors.

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

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

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

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Analysis of covariance includes at least one ________ independent variable and at least one ________ independent variable.

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Which statement is correct concerning one-way ANOVA?

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If you are estimating η2,you are at which step in the procedure for conducting one-way analysis of variance?

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________ is an ANOVA technique using two or more metric dependent variables.

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Draw the ANOVA interactive cases listed below (Figure 16.4 in the text).Name your dependent variable Y and assume that there are two factors,X1 with three levels (X11,X12,and X13),and X2 with two levels (X21 and X22).Briefly discuss/describe the interaction shown in each of your drawings. 1.no interaction 2.ordinal interaction 3.disordinal interaction (noncrossover) 4.disordinal interaction (crossover)

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An interaction effect occurs when the effect of an independent variable on a dependent variable is different for different categories or levels of another independent variable.

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