1 Which of the following is a null hypothesis for the averages of three groups in a one-way, between

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1 Which of the following is a null hypothesis for the averages of three groups in a one-way, between-subject ANOVA?

1 H0: Average1 ? Average2= Average3

2 H0: Average1 ? Average2? Average3

3 H0: Average1 = Average2= Average3

4 H0: Average1= Average2? Average3

1 If the null hypothesis is rejected in a one-way ANOVA with three groups, we can infer that:

a There is a significant difference in means for each of the three possible group pairings

b There is no significant difference in means for each of the three possible group pairings

c There is probably at least one significant difference in means among the three possible group pairings

d There is a significant difference in means for at least two of the three possible pairings

2 The major difference between t-tests and ANOVAs is that ANOVAs:

a Deal with multiple groups

b Compare group variances

c Make different assumptions about the populations from which we sample

d None of the above

3 An important assumption in a one-way ANOVA is that:

a Observations are random

b Observations are independent

c Subjects are related

d There are equal numbers of observations in each group

Chapter 13: Factorial Analysis of Variance

5 Which is true regarding factorial ANOVA ?

a A problem with this analysis is that the error term (SSwithin) is larger compared to oneway ANOVA

b A major advantage with this analysis is the ability to test for the interaction between treatment groups

c As in a one-way ANOVA, there is only one null hypothesis to be tested

d Factorial ANOVA cannot be used in nonexperimental research situations

6 A fixed factor in a factorial ANOVA is one in which:

a Levels of the factor represent a small percentage of all possible levels of the factor in the real world

b The experimenter is interested in only naturally occurring factors such as gender, not treatment factors

c The researcher includes all levels of a factor that are of interest in the study

d The treatment group variance is held constant

7 An example of a random factor in a factorial ANOVA is:

a Studying the hydration effect of tea, coffee, juice, and cola because they are readily available, while other forms of hydration (energy drinks, beer, etc) are not considered

b Not holding treatment variance constant across the levels of a factor

c Randomly assigning subjects to one of three antidepressant treatment groups

d Assigning groups based upon political party preference

8 When the lines in a graph of the cell means are roughly parallel in factorial ANOVA, we can conclude that:

a Neither the main effect for factor A nor factor B is statistically significant

b Main effects for factor A and factor B are statistically significant

c The interaction effect of factor A and factor B is statistically significant

d The interaction effect of factor A and factor B is not statistically significant

Chapter 17: Analysis of Covariance

9 The primary goal of analysis of covariance (ANCOVA) is to:

a Control for differences to determine if participant characteristics are statistically different

b Determine differences among groups while controlling for or removing the effects of some characteristics

c Increase the statistical power of experimental designs by increasing the error variance

d Measure the differences in some participant characteristics after the experiment has been conducted

10 Which of the following would be an example of a valid covariate in an ANCOVA analysis?

a IQ scores on students measured before implementing different reading comprehension programs

b Anxiety scores on subjects after implementing drug treatment interventions for

depression

c Racial bias of subjects prior to implementing a blood pressure reduction study

d Motivation level of subjects after implementing a smoking cessation intervention