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Statistics for Behavioral Sciences Exam 3 Part 2
This deck covers key concepts and questions related to two-factor ANOVA and correlation in statistics for behavioral sciences.
An interaction in a two-factor, independent-measured ANOVA can be seen from the graph of the two factors when _________________.
they are not parallel, and or they intersect.
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Key Terms
Term
Definition
An interaction in a two-factor, independent-measured ANOVA can be seen from the graph of the two factors when _________________.
they are not parallel, and or they intersect.
In a two-factor, independent-measures ANOVA, if SS between treatments = 67, SSA = 12, and SSB = 15, what is SSA×B?
40
In a two-factor, independent-measures ANOVA, with each factor having the same number of levels, if dfA×B = 4, how many levels does each factor have?
3
What happens in the first stage of a two-factor ANOVA?
The total variability is divided into “between-treatments” and “within-treatments.”
In a two-factor, independent-measures ANOVA, when is FA guaranteed to be equal to FB?
when MSA = MSB; Because the denominators of FA and FB are equal, the two F-ratios are the same whenever their numerators are equal, i.e. MSA = MSB. SS...
Why is testing a simple main effect in a two-factor ANOVA essentially the same thing as a single factor ANOVA?
Because we are restricting data to the first row of the data matrix.
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| Term | Definition |
|---|---|
An interaction in a two-factor, independent-measured ANOVA can be seen from the graph of the two factors when _________________. | they are not parallel, and or they intersect. |
In a two-factor, independent-measures ANOVA, if SS between treatments = 67, SSA = 12, and SSB = 15, what is SSA×B? | 40 |
In a two-factor, independent-measures ANOVA, with each factor having the same number of levels, if dfA×B = 4, how many levels does each factor have? | 3 |
What happens in the first stage of a two-factor ANOVA? | The total variability is divided into “between-treatments” and “within-treatments.” |
In a two-factor, independent-measures ANOVA, when is FA guaranteed to be equal to FB? | when MSA = MSB; Because the denominators of FA and FB are equal, the two F-ratios are the same whenever their numerators are equal, i.e. MSA = MSB. SSA = SSB only guarantees equal F-ratios when we also have dfA = dfB. See 14.2: An Example of the Two-Factor ANOVA and Effect Size. |
Why is testing a simple main effect in a two-factor ANOVA essentially the same thing as a single factor ANOVA? | Because we are restricting data to the first row of the data matrix. |
What information can we obtain from a simple main effect analysis in a two-factor ANOVA? | a. An evaluation of the effects of one factor b. An evaluation of one factor’s interaction with the second factor |
In a particular independent-measures design, two treatment groups were present, but the researcher noticed a high level of variability within each group, which led to a t-statistic that was too low. Upon further investigation, the researcher noticed that there were consistent individual differences, in that male scores were consistently higher than the female scores in both treatment groups. What can be done to salvage this study? | The researcher can use the same data, create a second factor of gender, split the treatment groups into two subgroups, and perform a two-factor ANOVA. |
A two-factor study has 3 levels of Factor A and 4 levels of Factor B. Because the ANOVA produces a significant interaction, the researcher decides to evaluate the simple mean effect of Factor A for each level of Factor B. How many F-ratios will this require? | 4 |
A researcher runs an independent-measures design for two treatment groups. The variability within each group is high, so the researcher splits each group by the participant variable of gender and attempts to run a factorial design ANOVA. The variability within each group is still high. What can the researcher conclude? | Gender was not an individual difference in the original treatment groups. |
A researcher introduces a second factor due to individual differences to create a factorial design from an independent-measures design. Why can this help the researcher draw conclusions about the data set? | It can reduce the variability within the treatment groups. |
Which of the following is measured and described by a correlation? | A correlation measures and describes three things: the direction of a relationship, the form of a relationship, and the strength of a relationship. |
The relationship between age and height in trees is most likely a _ correlation. | positive; In a positive correlation, the two variables tend in the same direction. In this case, as age increase, height tends to increase as well. |
Which of the following values represents a perfect correlation? | 1 and -1.00 |
The population of a bacteria colony is measured at 3:00, 3:15, and 3:30. The corresponding population values are 40, 80, and 160. Explain why this does or does not have a linear correlation. | This does not have a linear form because the population does not increase by the same amount every fifteen minutes. |