# EDRM 711 Midterm

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1. Total Means - SStot
The measure of an individual's score compared to the grand mean. sum((x11.-x...)...(xii.-x...)

df=n-1
2. Between Group Means - SSbg
The measure of a group's mean compared to the grand mean. sum((x.1.-x..)...(x.i.-x...)

• df=k-1
• MSbg=SSbg/dfbg
3. Within Group Means - SSwg
The measure of an individual's mean compared to the group's mean. sum((x11-x.1)..(xii-x.i)

df= n-k

MS=SSwg/dfbg
4. F-statistics
F=MSbg/MSwg
5. Cohen's D values
• 0.2 - small
• 0.5 - medium
• 0.8 - large
6. Cohen's f values
• 0.1 - small
• 0.25 - medium
• 0.4 - large
7. Interaction Types
Disordinal: non-parallel with an intersection

Ordinal: non-parallel with no intersection

No interaction: parallel lines
8. SSwg for factorial ANOVA
SSwg=SSerror= Sum of the individual deviations from the cell means.

dfwg=dferror=N-a*b=(n11-1)+(n12-1)+(n21-1)+(n22-1)

MSwg=MSerror=SSwg/dfwg
9. SSa*b
Sum of cell mean-row margin+column margin+grand mean)2 for all columns and rows.

dfa*b=(a-1)(b-1)

MSa*b=SSa*b/dfa*b
10. Mathematical Model for factorial ANOVA
yijk= μ +α j + β k +φ jk + eijk

μ = overall average in the population j

α= effect of being in jth achievement levelj

μ +α = population average for the jth achievement levelk

β= effect of being in kth CAI methodk μ + β = population mean for kth CAI methodjk

φ = effect of having the jkth combination of achievement level and CAI methodj k jk

μ +α + β +φ = population mean for the jkth combination ofachievement level and CAI method ijk

e = individual error
11. Key to the factorial ANOVA equation
yijk= μ +α j + β k +φ jk + eijk

• α=SSa
• β= SSb
• μ +α + β +φ = SSa*b
12. Full Regression SS
• Type III or unique SS
• Adjust each effect for all other effects in the design to obtain its unique contribution (nothing is being counted twice)
13. Experimental SS
Type II estimates main effects adjusting for the other main effects, but ignoring the interaction. Estimates the interaction adjusting for main effects. SS for A and B are too big. A and B are not unique, but A*B is.
14. Hierarchical SS
• Type I
• Uses theory or previous research to establish order for the effects, Adjusts each effect only for those preceding it in order.
15. Repeated Measures ANOVA - SSbg
Sum of the mean for time group and the grand mean to the jth group
16. Repeated Measures ANOVA - SSwg
Block score minus average score at each time point
17. Repeated Measures ANOVA - SSbl
Row block minus grand mean
18. Repeated Measures ANOVA - SSerror
SSerror=SSwg-SSbl - how much error gets pulled out from the blocks
19. Repeated Measures ANOVA - MSerror
SSerror/dferror = SSerror/(N-1)(k-1)

where N= # of blocks and k=# of time points
20. Repeated Measures ANOVA - F-stat
F=MSbg/MSerror

df=(k-1, (N-1)(k-1))
21. Repeated Measures ANOVA - Sphericity
E is less than or equal to 1. The closer E is to 1, the smaller the violation of the sphericity assumption.

If close to or equal to one, do not adjust F values
22. Nominal alpha
Level of significance - type 1 error rate (If assumptions are not violated)
23. Actual alpha
Percentage of making a type 1 error when at least 1 assumption has been violated. Test statistic is robust if actual alpha is very close to nominal alpha.
24. Experimental alpha
The alpha level set for the whole study (usually 0.05)
25. orthogonal contrast
Non-independent contrasts
26. Type II Error
Falsely rejecting the a true null hypothesis
 Author: tnrose87 ID: 202914 Card Set: EDRM 711 Midterm Updated: 2013-02-26 06:45:48 Tags: statistics Folders: Description: edrm Show Answers: