spss_chapter8 - 8 ! % % # 2% $ # (Two-way ANOVA) + % # %, 2...

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Unformatted text preview: 8 ! % % # 2% $ # (Two-way ANOVA) + % # %, 2 % $ # # % Nominal Scales % #% Interval Scale ., $% / #% % %$ # #A % %# %$ # #B # # A $ ## 0 p % # # B$ ## 0 q % $ ,# /"# p x q Factorial Design # #A 3% # #B 4 % $ 3 x 4 Factorial Design $% %, 3 # # "# # # A, B C (Three-way ANOVA) / 3 % ANOVA 3 % # .# 4 5% # %, 2 % ., % 1% ,$ 4& 5% # 2% % 1% # 1. H0 : aj = 0 ! H1 : aj 0 2. H0 : bk = 0 ! H1 : bk 0 3. H0 : (ab)jk = 0 H1 : (ab)jk 0 .# j .# j .# k .# k ! .# j .# j "# $ % # & k k # $#3 2 5 , npq SSTO = npq i =1 j=1k =1 n 2 Yijk 2 i =1 j =1k =1 Yijk 2 npq npq q SSA p = j =1 i =1k =1 Yijk nq - i =1 j =1k =1 Yijk npq 118 np 2 npq 2 / SPSS &# " .# - SSB q = k =1 i =1 j =1 Yijk np p - i =1 j =1k =1 Yijk 2 npq n q 2 SSAB = npq i =1 j=1k =1 2 Yijk j =1 2 i =1k =1 Yijk np q nq k =1 i =1 j =1 Yijk np npq + i =1 j =1k =1 Yijk 2 npq n pq i =1 SSWcel = MSA = npq i =1 j=1k =1 2 Yijk Yijk n j=1k =1 MSB = MSAB = MSWcel = 3 SSA p1 SSB q1 SSAB (p 1)(q 1) MSWcel pq(n 1) SS 1. A 2. B 3. AB 4. Within Cell 5. Total F 3 8.1 # E 5 - df SSA p-1 SSB q-1 SSAB (p - 1)(q - 1) SSWcell pq(n - 1) 44 SSTO F @$ MS MSA MSB MSAB MSWcell F [1]/[4] [2]/[4] [3]/[4] % 3 %A . % .# # .# % B# 0%, % &"# / # % C D5 B 8 # 119 .# # G . .# # A 160 156 170 169 151 168 177 155 143 %, "# 134 136 144 149 158 159 174 131 127 . 102 174 98 85 93 80 84 88 83 ,3 85 73 111 107 62 99 144 103 92 % .# size color score / E . .# # C6 + %1 . G, %2 . %3 . A .# # C4 + %1 , %2 %3 . %4 3, $ #% % C 8-10 - % *Analyze+ - # *General Linear Model+ "# , - # *Univariate...+ $ C& # 8.1 120 / SPSS &# " .# - "# % /# *Dependent Variable :+ , "# % *score+ % # /# *Fixed Factor(s) :+ "# *Random Factor(s) :+ / .# % # ,% *color+ *size+ 0 fix effect %, /# *Fixed Factor(s)+ 3 & ! -5 + !J *Post Hoc...+ K $ 3% & ! -5 "# + $ # ## " ## # $ /# *Factor(s) :+ # - /# *Post Hoc Tests for :+ # $ "# # % C& # 8.2 C& # "# %, % *Add+ "# % L % E % &% M 0 %, *Continue+ % %, # #% 0 # 8.2 !J *Plots...+ # 8 # 121 C& % J! "##" N G *Model...+ 0 J! 3 % 3 % "# 4& Main effect 3 % !J *Contrast...+ / $ !J *Save...+ 3 % % N LO .# !J *Options...+ 3 % "# &", P N % # B %& M % , 3 + # 8.3 # E % &% M 4 .# ! Tests of Between-Subjects Effects Dependent Variable: SCORE Type III Sum Source of Squares Corrected Model 33388.000a Intercept 568516.000 SIZE 171.500 COLOR 28716.222 SIZE * COLOR 4500.278 Error 9546.000 Total 611450.000 Corrected Total 42934.000 df 11 1 2 3 6 24 36 35 Mean Square F 3035.273 7.631 568516.000 1429.330 85.750 .216 9572.074 24.066 750.046 1.886 397.750 Sig. .000 .000 .808 .000 .125 a. R Squared = .778 (Adjusted R Squared = .676) C& # 8.4 122 / SPSS &# " .# - B$ E . .# # 3 5 F-test 0.216 % 3 %A % .808 K .05 % "#. .# # %B# % .# B- . # %# % 3 %A . .# # % B# % .# B- . # .# # 3 5 F-test 24.066 % 3 %A % .000 K # .01 % "# .# # %B# % .# B- . # %# % 3 %A .01 .# # %B# % .# B- . # E % &% M . .# # 3 5 F-test 1.886 % 3 %A % .125 K .05 E % &% M . .# # B # % .# B- . # $B % .# # % 3 %A $ 3B & ! -5 .# # &$ 5 Multiple Comparisons Dependent Variable: SCORE Scheffe Mean Difference (I-J) Std. Error 15.2222 9.4015 62.4444* 9.4015 63.6667* 9.4015 -15.2222 9.4015 47.2222* 9.4015 48.4444* 9.4015 -62.4444* 9.4015 -47.2222* 9.4015 1.2222 9.4015 -63.6667* 9.4015 -48.4444* 9.4015 -1.2222 9.4015 (J) COLOR 2.00 3.00 4.00 2.00 1.00 3.00 4.00 3.00 1.00 2.00 4.00 4.00 1.00 2.00 3.00 Based on observed means. (I) COLOR 1.00 Sig. .468 .000 .000 .468 .001 .000 .000 .001 .999 .000 .000 .999 95% Confidence Interval Lower Bound Upper Bound -13.0237 43.4681 34.1986 90.6903 35.4208 91.9125 -43.4681 13.0237 18.9763 75.4681 20.1986 76.6903 -90.6903 -34.1986 -75.4681 -18.9763 -27.0237 29.4681 -91.9125 -35.4208 -76.6903 -20.1986 -29.4681 27.0237 *. The mean difference is significant at the .05 level. C& # 8.5 8 # 123 E .# # % "# % ., % & ! -5B ,3 , B "# % . L "# % 3, E % &% M % , Estimated Marginal Means of SCORE 180 160 140 120 COLOR 1.00 Estimated Marginal Means 100 2.00 3.00 80 1.00 2.00 3.00 4.00 SIZE Estimated Marginal Means of SCORE 180 160 140 120 SIZE Estimated Marginal Means 100 1.00 2.00 80 1.00 2.00 3.00 4.00 3.00 COLOR C& # 8.6 ...
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This note was uploaded on 09/24/2010 for the course MBA 100 taught by Professor - during the Summer '10 term at Chulalongkorn University.

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