Two-Way ANOVA 1 (2) Flashcards
Which type of F statistic values are more likely to be significant?
Larger F statistic values.
What would happen if we were to increase the separation between the mean of each condition of the independent variable?
The F statistic value would increase.
Which type of F statistic value would result from the existence of a relatively small distance between the mean of each condition of the independent variable?
A relatively small F statistic value.
Which type of F statistic value would result from there being a relatively large distance between the mean of each condition of the independent variable?
A relatively large F statistic value.
What would happen if we were to increase the within-group variance for each condition of the independent variable?
The F statistic value would decrease and be less likely to prove significant.
Which type of F statistic value would result from the existence of a relatively small within-group variance for each condition of the independent variable?
A relatively large F statistic value.
Which type of F statistic value would result from there being a relatively large within-group variance for each condition of the independent variable?
A relatively small F statistic value.
What is the first step involved in calculating the F statistic?
Calculating the SSM (model sum of squares).
To what does the term ‘SSM’ refer?
To how much of the variance observed within a set of data can be explained by the difference between the means of each separate condition of the independent variable.
How can the SSM be calculated?
By squaring the difference between the mean of each separate condition of the independent variable and the group mean, multiplying each of these values by the number of participants involved in each group, and adding each of these values together.
What is the second step involved in calculating the F statistic?
Calculating the SSR (residual sum of squares).
To what does the term ‘SSR’ refer?
To the difference between the means of each separate condition of the independent variable and the individual datapoints involved in each separate condition, squared and summed.
