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Psychology

PSYC 3000

Bruce Hutcheon

Winter

Description

Error
Xji – M = Tj+ Eji
Total Treatment
If the null hypothesis for simple ANOVA is true then the means of the different samples in the design form a sampling distribution for
the mean. True.
In ANOVA, it makes sense to pool variances only if the null hypothesis (that the treatment does not affect the mean value of the
dependent variable) is true. False
In ANOVA, it only makes sense to pool variances when the treatment does not affect the population variance. True
In simple ANOVA, the "within" estimate of population variance is derived from the variances of the samples. True
The F ratio used in ANOVA cannot have values smaller than 1. False
In ANOVA we pool together sample variances to form a "within" estimate of population variance because if the null hypothesis that
the treatment does not affect the mean is true, the samples form a sampling distribution. False
Suppose a balanced ANOVA design has n=25. If the null hypothesis that the treatment does not affect the mean is true, and the
variance of the sample means is 49, what is the "between" estimate for the population variance? 49*25
If you had results from a simple ANOVA design with k=2, you could run either an F-test with 1 between-groups degrees of freedom
or an independent-samples t-test and expect to get exactly the same p-value. True
For a simple ANOVA with k=2, the between degrees of freedom is 1. True
Click beside one or more of the designs listed below to indicate which ones are best analyzed with a 1-way ANOVA. 1 interval DV,
and 1 nominal IV with 5 levels.
In a 2-way ANOVA, what is the best definition of the F-distribution that is used to test the main effect of A?. The distribution of
possible F-values you might get if the marginal means for treatment A do not depend on which level of A you are at.
In a 2-way factorial design, if the test of a particular main or simple effect yields F=2, then you should automatically reject the
corresponding null hypothesis. False
In a 2-way factorial design with a = 4, b = 6, and n = 5, how many observations contribute to each marginal mean for treatment B? 20
Suppose you have a 2-way factorial design with a = 4, b = 6, and n = 10 and you want to test the main effect of treatment A. How
many different cell means are involved in constructing the estimate of population variance that occurs in the numerator of the
appropriate F ratio? NONE
Suppose you have a 2-way factorial design with a = 4, b = 6, and n = 10 and you want to test the main effect of treatment A. How
many different marginal means are involved in constructing the estimate of population variance that occurs in the numerator of the
appropriate F ratio? 4
Suppose you have a 2-way factorial design with a = 4, b = 6, and n = 10 and you want to test the simple effect of treatment B at level 1
of treatment A. How many different cell means are involved in constructing the estimate of population variance that occurs in the
numerator of the appropriate F ratio? 6
In a 2-way factorial design with a = 4, b = 6, and n = 5, how many variances need to be pooled together to produce the estimate of
population variance that appears in the bottom of the F ratio? 24
In a 2-way design, which treatment effect is tested using the variance of the marginal means for Treatment B? Main Effect of
treatment B.
In a 2-way ANOVA with a = 2 and b = 4, if the means in cells 12 and 22 are the same, this would indicate that there is no simple
effect of B on the dependent variable at level 2 of A. False
If the lines in an interaction plot are NOT parallel then there is a significant interaction between the independent variables. False
In the interaction plot for a 2-way design, if there is an apparent interaction then at least one apparent simple effect must be present.
True
In a 2-way design, if there appear to be a main effects of both factors then an interaction should also be visible. False
In the interaction plot for a 2-way design, if there is an apparent interaction then there must be at least one main effect present. False
In a 2-way design, if the results in an interaction plot appear as 2 distinct horizontal lines, then there are no apparent main effects of
the independent variables on the dependent variables. False
How many possible simple effects are possible in a 2x3 design which is meant to test whether psychological interventions or gender
affect workplace stress? 5
Suppose that, for a 2x2 design, an interaction plot has 1 horizontal line and 1 diagonal line. Which of the following descriptions would
be wrong? The simple effects of treatment A are independent of treatment B.
In a 1-way ANOVA with k = 5 and n = 10, how many distinct error terms, eji, can be calculated for participants at level 2 of the
treatment? 10
In a 1-way ANOVA with k = 5 and n = 10, how many distinct error terms, eji, can be calculated for participants at level 5 of the
treatment? 10
In a 1-way ANOVA with k = 5 and n = 10, how many distinct treatment terms, tau_j, can be calculated for participants at level 5 of
the treatment? 1
In a 1-way ANOVA with k = 5 and n = 10, how many distinct treatment terms, tau_j, can be calculated for participants across the
entire design? 5
A measure of ability to cooperate with others was recorded for young children from 1-, 2-, and 3-child families. The mean cooperation
level for children in 3-child families was found to be 2 units above the grand mean and one particular child in one of these families
was found to score 3 units about the grand mean. What is the error, e_3i, term associated with this child? e_3i = 1
From which part of the structural model is SSbetween derived? The deviation between treatment means and the grand mean
From which part of the structural model is SStreatment derived? The deviation between treatment means and the grand mean.
From which part of the structural model is SSwithin derived? The error associated with measurements.
In a 1-way ANOVA with 8 treatment groups and 10 participants per group, what is the within degrees of freedom? 72
In the structural model for a 1-w

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