n educational psychologist is examining response times to an on-screen stimulus. The researcher believes there might be a weak effect from age, but expects a more pronounced effect for different color contrasts. She decides to examine a black on white (B/W) combination compared to 2 alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (in milliseconds): B/W R/W Y/B 16–17 8 44 21 20 17 32 21 24 22 24 45 5 9 35 21 26 8 33 19 13 23 28 19 7 18–19 37 17 35 39 36 19 15 47 24 13 16 11 19 23 15 32 24 32 37 24 32 37 29 46 20–21 38 17 22 26 23 15 26 20 41 29 26 19 29 20 31 27 18 37 44 29 41 40 27 44 Using MS Excel, conduct a 2-way ANOVA with α=0.05α=0.05. Fill in the summary table. The last column in the table below is read as, "Partial Eta-squared " and is a concept that was NOT covered in the lectures. Partial ηη 2 is used when there is a chance the data is not independent (click here to read more if interested) Computing the values for "Partial ηη 2" is not difficult. Simply divide SSeffect by the sum of SSeffect and SSerror. For example, Partial ηη 2(A) = SSA /(SSA + SSerror) P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal places. Source SS df MS F-ratio P-value Partial η2η2 Age (AA) 2 Color (BB) 2 Interaction (A×B)(A×B) 4 Error 63
An educational psychologist is examining response times to an on-screen stimulus. The researcher believes there might be a weak effect from age, but expects a more pronounced effect for different color contrasts. She decides to examine a black on white (B/W) combination compared to 2 alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (in milliseconds):
B/W | R/W | Y/B | ||
---|---|---|---|---|
16–17 | 8 44 21 20 17 32 21 24 |
22 24 45 5 9 35 21 26 |
8 33 19 13 23 28 19 7 |
|
18–19 | 37 17 35 39 36 19 15 47 |
24 13 16 11 19 23 15 32 |
24 32 37 24 32 37 29 46 |
|
20–21 | 38 17 22 26 23 15 26 20 |
41 29 26 19 29 20 31 27 |
18 37 44 29 41 40 27 44 |
Using MS Excel, conduct a 2-way ANOVA with α=0.05α=0.05. Fill in the summary table.
The last column in the table below is read as, "Partial Eta-squared " and is a concept that was NOT covered in the lectures. Partial ηη 2 is used when there is a chance the data is not independent (click here to read more if interested) Computing the values for "Partial ηη 2" is not difficult. Simply divide SSeffect by the sum of SSeffect and SSerror. For example, Partial ηη 2(A) = SSA /(SSA + SSerror)
P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal places.
Source | SS | df | MS | F-ratio | P-value | Partial η2η2 |
---|---|---|---|---|---|---|
Age (AA) | 2 | |||||
Color (BB) | 2 | |||||
Interaction (A×B)(A×B) | 4 | |||||
Error | 63 |
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