Complete the following ANOVA summary table for a two-factor fixed-effects ANOVA, where there are ve levels of factor A (school) and six levels of factor B (curriculum design). Each cell includes 11 students. Use a signicance level ofa = 0.05. Round values for SS and MS to 3 decimal places as needed. Round p-value to 4 decimal places. Source 88' df MS F p A B 5566.2 A X B 16289.7 Error 156900 TOTAL 1841026 Decision for the main effect of factor A: O reject the null H01 O fail to reject the null H01 Decision for the main effect of factor B: O reject the null H02 O fail to reject the null H02 Decision for the interaction effect between factors A and B: O reject the null H03 0 fail to reject the null H03 Here is an ANOVA summary table for a 2-way fixed-effects balanced design. Using =FINV( J in Excel, find the critical values for each hypothesis test at both the or = 0.05 and oz = 0.01 significance levels. Source SS df MS F F0.05,df1,df2 F0.01,df1,df2 A 2531.9 2 1265.95 3.254 B 4579.2 6 763.2 1 .962 A X B 7161.4 12 596.783 1.534 Error 114366 294 389 TOTAL 1286385 314 Round to four decimal points. Finally, what was the sample size for each cell in this 2-factor design? 7; : Hint:Add 1 to the total degrees of freedom to compute the overall total number of data values in the table. Next, add 1 to the dfforA 8: B to compute the actual number of groups in each row category (A) & column category {8). Now to compute the sample size simply take the overall total {df+ 1) divided by the PRODUCT of the number of row and column groups. This will produce "n" or the number of samples in each grouping. Next Complete the following ANOVA summary table for a two-factor fixed-effects ANOVA, where there are five levels of factor A (school) and three levels of factor B (curriculum design). Each cell includes 11 students. Round values for SS and MS to 3 decimal places as needed. Round p-value to 4 decimal places. Source SS df MS F P A 4798.1 1.976 0.101 B 3660.9 3.016 0.052 A x B 7823.9 1.611 0.126 Error TOTAL 107332.9An 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 [Ble combination compared to 2 alternatives: red on white (WW) and yellow on blue [WE]. Here is the data for response times {in milliseconds): 115-1}r 18-19 20-21 BM RM 26 TI" 10 23 31 19 22 20 16 16 22 20 36 43 11 31 15 1? 1? 4? 21 19 13 35 25 3? 34 39 26 15 18 36 28 30 28 40 22 28 25 26 19 19 24 25 1? 28 40 18 \"'3 22 24 43 19 3 20 33 2 23 31 23 28 45 36 31 36 35 42 25 16 38 2? 42 39 Using MS Excel. conduct a 2-way ANOVA with o: = 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 7] 2 is used when there is a chance the data is not independent [click here to read more if interested '3') Computing the values for "Partial '3] is not difficult. Simply divide Sseffect by the sum of Sseffect and SSerror- For example, Partial 1} 2(A) = SSA {[SSA + SSermrj P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal places. Partial Source 55 at MS Pvalue \"'12 Age (A) 2 Color {B} 2 Interaction 4 (A x B) Error 63