MTB > read '92hw2p1.dat' c1 36 ROWS READ C1 26 23 28 19 . . . MTB > set c2 DATA> (1:2)18 DATA> end MTB > set c3 DATA> 2(1:3)6 DATA> end MTB > anova c1 = c2|c3 Factor Type Levels Values C2 fixed 2 1 2 C3 fixed 3 1 2 3 Analysis of Variance for C1 Source DF SS MS F P C2 1 196.00 196.00 12.42 0.001 C3 2 156.22 78.11 4.95 0.014 C2*C3 2 1058.67 529.33 33.55 0.000 Error 30 473.33 15.78 Total 35 1884.22 MTB > print c1 C1 26 23 28 19 18 25 30 25 27 36 28 24 6 11 17 10 14 19 15 24 25 16 22 21 24 29 23 26 27 21 31 29 35 38 34 30 MTB > set c10 DATA> (0:1)18 DATA> end MTB > print c10 C10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 MTB > set c11 DATA> 6(0),6(1),12(0),6(1),6(0) DATA> end MTB > print c11 C11 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 MTB > set c12 DATA> 12(0),6(1),12(0),6(1) DATA> end MTB > print c12 C12 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 MTB > let c13 = c10*c11 MTB > let c14 = c10*c12 MTB > regress c1 5 c10 c11 c12 c13 c14 The regression equation is C1 = 23.2 - 2.67 C10 + 5.17 C11 - 10.3 C12 - 0.67 C13 + 22.7 C14 Predictor Coef Stdev t-ratio p Constant 23.167 1.622 14.29 0.000 C10 -2.667 2.293 -1.16 0.254 C11 5.167 2.293 2.25 0.032 C12 -10.333 2.293 -4.51 0.000 C13 -0.667 3.243 -0.21 0.839 C14 22.667 3.243 6.99 0.000 s = 3.972 R-sq = 74.9% R-sq(adj) = 70.7% Analysis of Variance SOURCE DF SS MS F p Regression 5 1410.89 282.18 17.88 0.000 Error 30 473.33 15.78 Total 35 1884.22 SOURCE DF SEQ SS C10 1 196.00 C11 1 150.22 C12 1 6.00 C13 1 288.00 C14 1 770.67 Unusual Observations Obs. C10 C1 Fit Stdev.Fit Residual St.Resid 10 0.00 36.000 28.333 1.622 7.667 2.11R R denotes an obs. with a large st. resid. MTB > write 'dum2way.dat' c1-c14 * NOTE * No data in column MTB > corr c10-c14 C10 C11 C12 C13 C11 0.000 C12 0.000 -0.500 C13 0.447 0.632 -0.316 C14 0.447 -0.316 0.632 -0.200