CHAPTER 18: ANALYSIS OF VARIANCE (TWO WAY) Key Terms Two-way ANOVA A more comple
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CHAPTER 18: ANALYSIS OF VARIANCE (TWO WAY) Key Terms Two-way ANOVA A more complex type of analysis of variance that tests whether differences exist among population means categorized by two factors or independent variable. Main effect-The effect of a single factor when any other factor is ignored. Simple effect effect of one factor at a single level of another factor Interaction-The product of inconsistent simple effect Text Review In two-way ANovA, there are four different types of means. Column means represent the effect of one variable when the other is ignored. In the text example, column means represent reaction times for is ignored. Slight difference among each number of confederates present when (1) More substantial differences reflect the these column means could be attributed to (2) main effect of the number of confederates on reaction time. In ANOVA, the effect of a single factor, Row means represent the when any other factor is ignored, is the (3) reaction times for gender when crowd size is ignored. Again, slight differences could be attributed to of gender on reaction time. The cell means chance, but larger chances reflect a (4) also referred to as treatment-combination means, reflect any effect due to the interaction of the two factors being studied. The final average of the column means or row means equals the overall or (5) You may recall from Chapter 22 that in one-way ANOVA, a single Fratio is used to test the null hypothesis. In a two-way ANOVA, three different null hypotheses are tested, one at a time, with three F ratios: F column, F row, F action. In each F ratio, the numerator represents (6) This The denominator term represents for subjects treated similarly in the same group only (8) With so many similarities between one-way and two-way ANOVA, (9) s the most obvious different feature of the two-way ANOVA. Two factors are said to interact if the effects of one actor are not consistent for all the levels of the second factor. The presence of interaction may highlight important issues for future research. Interaction can be clarified by examining the concept of simple effect, the effect of one variable at a single level of another variable. Interaction is the product of (10) The assumptions for the two-way ANOVA are similar to those for one-way ANOVA. All (11) are assumed to be normally distributed with (12) (13) You needn't to be too concemed about violations of these assumptions as long as all group are fairly large Although more complex ANovA is possible with a larger number of factors, the goal of the researcher should be to use the simplest design that will adequately answer the research question.Explanation / Answer
Chapter II: Analysis of variance two way
The fill ups are as follows:
1. Reaction time is ignored
2. Chance
3. Main effect
4. main effect of gender on reaction time
5. Grand mean
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