STAT 305 Acton School of Business

Two Examples of ANOVA Example 1: This is the age (response variable) by diagnosis (factor or explanatory variable) that was discussed in lecture on 5 Nov. I recoded the diagnosis codes as 0=Normal, 1=ACIS, and 2=AdCa. I entered the data into Minitab

Species Weight Length 1 242 30 1 290 31.2 1 340 31.1 1 363 33.5 1 430 34 1 450 34.7 1 500 34.5 1 390 35 1 450 35.1 1 500 36.2 1 475 36.2 1 500 36.2 1 500 36.4 1 600 37.2 1 600 37.2 1 700 38.3 1 700 38.5 1 610 38.6 1 650 38.7 1 575 39.5 1 685 39.2 1

Speed 28 22 36 26 28 28 26 24 32 30 27 24 33 21 36 32 31 25 24 25 28 36 27 32 34 30 25 26 26 25 -44 23 21 30 33 29 27 29 28 22 26 27 16 31 29 36 32 28 40 19 37 23 32 29 -2 24 25 27 24 16 29 20 28 27 39 23

TIME CON CITY BRINK 1 2224277 6729 0 2 1892672 5751 0 3 1468074 6711 0 4 1618966 7069 0 5 1509195 7134 0 6 1511014 5954 0 7 1506977 5447 0 8 1520443 6558 0 9 1070936 5222 0 10 1794191 4150 0 11 1602841 6765 0 12 1246483 6681 0 13 1330143 7016 1 14 1

City Yr1972 Yr1968 N.Y. 0.45 0.42 L.A. 0.5 0.5 Chicago 0.52 0.52 Philadelphia 0.45 0.45 Detroit 0.46 0.43 San Francisco 0.55 0.55 Boston 0.6 0.45 Pitt. 0.49 0.34 St. Louis 0.35 0.45 Connecticut 0.55 0.54 \"Wash., D.C.\" 0.52 0.42 Cinn. 0.53 0.51 Baltim

BeginCal EndCal BeginPlacebo EndPlacebo 107 100 123 124 110 114 109 97 123 105 112 113 129 112 102 105 112 115 98 95 111 116 114 119 107 106 119 114 112 102 112 114 136 125 110 121 102 104 117 118 130 133

Species 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 Weight (g) Length3 (cm) 242 30 290 31.2 340 31.1 363 33.5 430 34 450 34.7 500 34.5 390 35 450 35.1 500 36.2 475 36.2 500 36.2 500 36.4 60

0 1 0 1 1 0 1 0 0 1 1 0 0 1 0 0 0 1 0 0 0 1 0 0 1 0 1 0 1 0 1 0 1 1 0 0 1 1 0 1 1 0 0 1 0 0 1 0 0 0

Freshmen Sophomores Juniors Seniors 2.5 2.3 3.5 2.3 2.2 1.6 2.9 2.5 1.4 2.8 1.6 2 2.6 3.2 3.3 3.1 2.4 2.4 3.6 2.7 1.4 3.4 3.1 3.9 2.4 2.4 3.2 3 2.6 3.4 2.6 3.9 2.3 3 3.7 3.8 2.9 3.4 3.8 3.8