Sharon Cabrera, Marc Ribas, Eloi Rodrigez, David Romero
In this work we have identified the preferences of a dozen people of different ages when they have to choose the perfect partner:
#Conjoint Analysis
library(conjoint)## Warning: package 'conjoint' was built under R version 3.2.4#Describe Factors and levels
att <-list(
ulls=c("clars","foscos"),
cabell=c("clar","foscos"),
fisic=c("Alt","Baix","Prim","Gras"),
caracter=c("Alegre","Seriòs","Nervios","Tranquil"),
mental=c("mes inteligent que tu","menys inteligent que tu","igual de inteligent que tu"),
personalitat=c("Divertit","Avorrit","Interessant","Carismatic"),
vestimenta=c("Hippie","A la Moda","Provocatiu","Elegant"),
higienePersonal=c("Net","Brut")
)#Full factorial design
profiles <- expand.grid(att)
head(profiles)## ulls cabell fisic caracter mental personalitat
## 1 clars clar Alt Alegre mes inteligent que tu Divertit
## 2 foscos clar Alt Alegre mes inteligent que tu Divertit
## 3 clars foscos Alt Alegre mes inteligent que tu Divertit
## 4 foscos foscos Alt Alegre mes inteligent que tu Divertit
## 5 clars clar Baix Alegre mes inteligent que tu Divertit
## 6 foscos clar Baix Alegre mes inteligent que tu Divertit
## vestimenta higienePersonal
## 1 Hippie Net
## 2 Hippie Net
## 3 Hippie Net
## 4 Hippie Net
## 5 Hippie Net
## 6 Hippie Nettail(profiles)## ulls cabell fisic caracter mental personalitat
## 6139 clars foscos Prim Tranquil igual de inteligent que tu Carismatic
## 6140 foscos foscos Prim Tranquil igual de inteligent que tu Carismatic
## 6141 clars clar Gras Tranquil igual de inteligent que tu Carismatic
## 6142 foscos clar Gras Tranquil igual de inteligent que tu Carismatic
## 6143 clars foscos Gras Tranquil igual de inteligent que tu Carismatic
## 6144 foscos foscos Gras Tranquil igual de inteligent que tu Carismatic
## vestimenta higienePersonal
## 6139 Elegant Brut
## 6140 Elegant Brut
## 6141 Elegant Brut
## 6142 Elegant Brut
## 6143 Elegant Brut
## 6144 Elegant Brut#Get a better esign
design <- caFactorialDesign(data=profiles,type="fractional",cards=25)#levels
print(design)#scenario## ulls cabell fisic caracter mental personalitat
## 10 foscos clar Prim Alegre mes inteligent que tu Divertit
## 211 clars foscos Alt Seriòs mes inteligent que tu Avorrit
## 333 clars clar Gras Alegre igual de inteligent que tu Avorrit
## 740 foscos foscos Alt Nervios igual de inteligent que tu Carismatic
## 884 foscos foscos Alt Tranquil menys inteligent que tu Divertit
## 1366 foscos clar Baix Seriòs mes inteligent que tu Carismatic
## 1479 clars foscos Baix Alegre igual de inteligent que tu Carismatic
## 1629 clars clar Gras Seriòs menys inteligent que tu Divertit
## 2090 foscos clar Prim Nervios igual de inteligent que tu Interessant
## 2597 clars clar Baix Nervios menys inteligent que tu Avorrit
## 2751 clars foscos Gras Tranquil mes inteligent que tu Interessant
## 2960 foscos foscos Gras Alegre menys inteligent que tu Carismatic
## 3181 clars clar Gras Nervios menys inteligent que tu Divertit
## 3544 foscos foscos Baix Seriòs menys inteligent que tu Interessant
## 3769 clars clar Prim Tranquil menys inteligent que tu Carismatic
## 4075 clars foscos Prim Nervios mes inteligent que tu Avorrit
## 4222 foscos clar Gras Tranquil igual de inteligent que tu Avorrit
## 4289 clars clar Alt Alegre menys inteligent que tu Interessant
## 4791 clars foscos Baix Tranquil igual de inteligent que tu Divertit
## 4876 foscos foscos Prim Alegre menys inteligent que tu Avorrit
## 5232 foscos foscos Gras Nervios mes inteligent que tu Carismatic
## 5233 clars clar Alt Tranquil mes inteligent que tu Carismatic
## 5382 foscos clar Baix Alegre mes inteligent que tu Divertit
## 5531 clars foscos Prim Seriòs igual de inteligent que tu Divertit
## 5714 foscos clar Alt Seriòs igual de inteligent que tu Avorrit
## vestimenta higienePersonal
## 10 Hippie Net
## 211 Hippie Net
## 333 Hippie Net
## 740 Hippie Net
## 884 A la Moda Net
## 1366 A la Moda Net
## 1479 A la Moda Net
## 1629 Provocatiu Net
## 2090 Provocatiu Net
## 2597 Elegant Net
## 2751 Elegant Net
## 2960 Elegant Net
## 3181 Hippie Brut
## 3544 Hippie Brut
## 3769 Hippie Brut
## 4075 A la Moda Brut
## 4222 A la Moda Brut
## 4289 A la Moda Brut
## 4791 Provocatiu Brut
## 4876 Provocatiu Brut
## 5232 Provocatiu Brut
## 5233 Provocatiu Brut
## 5382 Elegant Brut
## 5531 Elegant Brut
## 5714 Elegant Brut#Get the levels
levels <- c("clars","foscos","clar","foscos","Alt","Baix","Prim","Gras","Alegre","Seriòs","Nervos","Tranquil"
,"mes inteligent que tu","menys inteligent que tu","igual de inteligent que tu","Divertit",
"Avorrit","Interessant","Carismatic","Hippie","A la Moda","Provocatiu","Elegante","Net","Brut")
#Get the preference for each user/customer
pref <- c(1:25)#l'ordre amb les que la triaria
#Execute Conjoint analysis
#conjoint(matrix of preferences, design matrix, levels matrix)user1 <- Conjoint(pref,design, levels)##
## Call:
## lm(formula = frml)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0,59385 -0,11922 0,06249 0,14023 0,46646
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12,959288 0,106641 121,523 6,74e-13 ***
## factor(x$ulls)1 0,009025 0,106214 0,085 0,93466
## factor(x$cabell)1 0,127038 0,104421 1,217 0,26318
## factor(x$fisic)1 0,650471 0,190215 3,420 0,01114 *
## factor(x$fisic)2 -0,499930 0,190753 -2,621 0,03437 *
## factor(x$fisic)3 -0,068833 0,192147 -0,358 0,73073
## factor(x$caracter)1 0,266097 0,179823 1,480 0,18247
## factor(x$caracter)2 0,390076 0,190885 2,044 0,08030 .
## factor(x$caracter)3 -0,338417 0,188082 -1,799 0,11500
## factor(x$mental)1 -0,335913 0,149007 -2,254 0,05882 .
## factor(x$mental)2 -0,286194 0,147826 -1,936 0,09408 .
## factor(x$personalitat)1 -0,698629 0,180208 -3,877 0,00608 **
## factor(x$personalitat)2 -0,538893 0,184354 -2,923 0,02224 *
## factor(x$personalitat)3 0,112261 0,212457 0,528 0,61356
## factor(x$vestimenta)1 -4,743746 0,178865 -26,521 2,77e-08 ***
## factor(x$vestimenta)2 -1,573496 0,190357 -8,266 7,39e-05 ***
## factor(x$vestimenta)3 1,582699 0,191669 8,257 7,44e-05 ***
## factor(x$higienePersonal)1 -6,064082 0,109167 -55,548 1,61e-10 ***
## ---
## Signif. codes: 0 '***' 0,001 '**' 0,01 '*' 0,05 '.' 0,1 ' ' 1
##
## Residual standard error: 0,513 on 7 degrees of freedom
## Multiple R-squared: 0,9986, Adjusted R-squared: 0,9951
## F-statistic: 290,2 on 17 and 7 DF, p-value: 2,597e-08## [1] "Part worths (utilities) of levels (model parameters for whole sample):"
## levnms utls
## 1 intercept 12,9593
## 2 clars 0,009
## 3 foscos -0,009
## 4 clar 0,127
## 5 foscos -0,127
## 6 Alt 0,6505
## 7 Baix -0,4999
## 8 Prim -0,0688
## 9 Gras -0,0817
## 10 Alegre 0,2661
## 11 Seriòs 0,3901
## 12 Nervos -0,3384
## 13 Tranquil -0,3178
## 14 mes inteligent que tu -0,3359
## 15 menys inteligent que tu -0,2862
## 16 igual de inteligent que tu 0,6221
## 17 Divertit -0,6986
## 18 Avorrit -0,5389
## 19 Interessant 0,1123
## 20 Carismatic 1,1253
## 21 Hippie -4,7437
## 22 A la Moda -1,5735
## 23 Provocatiu 1,5827
## 24 Elegante 4,7345
## 25 Net -6,0641
## 26 Brut 6,0641
## [1] "Average importance of factors (attributes):"
## [1] 0,07 0,96 4,33 2,74 3,61 6,87 35,71 45,70
## [1] Sum of average importance: 99,99
## [1] "Chart of average factors importance"set.seed(123)
pref2 <-sample(1:25, 25, replace=F)
user2 <- Conjoint(pref2,design, levels)##
## Call:
## lm(formula = frml)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3,9175 -1,7522 -0,0615 1,2554 5,5845
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 13,82142 0,98651 14,010 2,23e-06 ***
## factor(x$ulls)1 0,57000 0,98256 0,580 0,58002
## factor(x$cabell)1 0,06619 0,96597 0,069 0,94729
## factor(x$fisic)1 7,11971 1,75964 4,046 0,00489 **
## factor(x$fisic)2 3,18664 1,76461 1,806 0,11390
## factor(x$fisic)3 -5,09926 1,77751 -2,869 0,02403 *
## factor(x$caracter)1 0,24627 1,66350 0,148 0,88648
## factor(x$caracter)2 -4,16533 1,76583 -2,359 0,05043 .
## factor(x$caracter)3 4,71855 1,73990 2,712 0,03011 *
## factor(x$mental)1 -0,31357 1,37843 -0,227 0,82655
## factor(x$mental)2 0,50042 1,36750 0,366 0,72522
## factor(x$personalitat)1 2,22902 1,66707 1,337 0,22301
## factor(x$personalitat)2 0,22683 1,70542 0,133 0,89793
## factor(x$personalitat)3 4,30347 1,96539 2,190 0,06471 .
## factor(x$vestimenta)1 -1,62461 1,65464 -0,982 0,35888
## factor(x$vestimenta)2 -2,52486 1,76095 -1,434 0,19475
## factor(x$vestimenta)3 2,22362 1,77308 1,254 0,25006
## factor(x$higienePersonal)1 2,17633 1,00988 2,155 0,06810 .
## ---
## Signif. codes: 0 '***' 0,001 '**' 0,01 '*' 0,05 '.' 0,1 ' ' 1
##
## Residual standard error: 4,745 on 7 degrees of freedom
## Multiple R-squared: 0,8787, Adjusted R-squared: 0,5843
## F-statistic: 2,984 on 17 and 7 DF, p-value: 0,07325## [1] "Part worths (utilities) of levels (model parameters for whole sample):"
## levnms utls
## 1 intercept 13,8214
## 2 clars 0,57
## 3 foscos -0,57
## 4 clar 0,0662
## 5 foscos -0,0662
## 6 Alt 7,1197
## 7 Baix 3,1866
## 8 Prim -5,0993
## 9 Gras -5,2071
## 10 Alegre 0,2463
## 11 Seriòs -4,1653
## 12 Nervos 4,7185
## 13 Tranquil -0,7995
## 14 mes inteligent que tu -0,3136
## 15 menys inteligent que tu 0,5004
## 16 igual de inteligent que tu -0,1868
## 17 Divertit 2,229
## 18 Avorrit 0,2268
## 19 Interessant 4,3035
## 20 Carismatic -6,7593
## 21 Hippie -1,6246
## 22 A la Moda -2,5249
## 23 Provocatiu 2,2236
## 24 Elegante 1,9259
## 25 Net 2,1763
## 26 Brut -2,1763
## [1] "Average importance of factors (attributes):"
## [1] 2,62 0,30 28,36 20,44 1,87 25,45 10,93 10,02
## [1] Sum of average importance: 99,99
## [1] "Chart of average factors importance"preffAll<- cbind(pref,pref2)
userAll<-Conjoint(preffAll,design,levels)##
## Call:
## lm(formula = frml)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12,3858 -3,9036 0,0963 4,2109 11,0654
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12,9527 0,9845 13,157 1,87e-14 ***
## factor(x$ulls)1 1,9158 0,9805 1,954 0,0595 .
## factor(x$cabell)1 -0,8018 0,9640 -0,832 0,4117
## factor(x$fisic)1 2,2043 1,7560 1,255 0,2185
## factor(x$fisic)2 -0,3676 1,7610 -0,209 0,8360
## factor(x$fisic)3 -1,3886 1,7738 -0,783 0,4395
## factor(x$caracter)1 0,5537 1,6601 0,334 0,7409
## factor(x$caracter)2 2,0822 1,7622 1,182 0,2461
## factor(x$caracter)3 1,9213 1,7363 1,107 0,2767
## factor(x$mental)1 0,3040 1,3756 0,221 0,8265
## factor(x$mental)2 2,0292 1,3647 1,487 0,1468
## factor(x$personalitat)1 -2,7363 1,6636 -1,645 0,1098
## factor(x$personalitat)2 1,4596 1,7019 0,858 0,3975
## factor(x$personalitat)3 0,4150 1,9613 0,212 0,8337
## factor(x$vestimenta)1 -2,8927 1,6512 -1,752 0,0894 .
## factor(x$vestimenta)2 -0,8950 1,7573 -0,509 0,6140
## factor(x$vestimenta)3 3,1643 1,7694 1,788 0,0832 .
## factor(x$higienePersonal)1 -2,0727 1,0078 -2,057 0,0479 *
## ---
## Signif. codes: 0 '***' 0,001 '**' 0,01 '*' 0,05 '.' 0,1 ' ' 1
##
## Residual standard error: 6,697 on 32 degrees of freedom
## Multiple R-squared: 0,448, Adjusted R-squared: 0,1547
## F-statistic: 1,528 on 17 and 32 DF, p-value: 0,147## [1] "Part worths (utilities) of levels (model parameters for whole sample):"
## levnms utls
## 1 intercept 12,9527
## 2 clars 1,9158
## 3 foscos -1,9158
## 4 clar -0,8018
## 5 foscos 0,8018
## 6 Alt 2,2043
## 7 Baix -0,3676
## 8 Prim -1,3886
## 9 Gras -0,4481
## 10 Alegre 0,5537
## 11 Seriòs 2,0822
## 12 Nervos 1,9213
## 13 Tranquil -4,5573
## 14 mes inteligent que tu 0,304
## 15 menys inteligent que tu 2,0292
## 16 igual de inteligent que tu -2,3332
## 17 Divertit -2,7363
## 18 Avorrit 1,4596
## 19 Interessant 0,415
## 20 Carismatic 0,8616
## 21 Hippie -2,8927
## 22 A la Moda -0,895
## 23 Provocatiu 3,1643
## 24 Elegante 0,6234
## 25 Net -2,0727
## 26 Brut 2,0727
## [1] "Average importance of factors (attributes):"
## [1] 9,34 6,49 13,82 19,52 11,55 13,78 15,24 10,25
## [1] Sum of average importance: 99,99
## [1] "Chart of average factors importance"caPartUtilities(preffAll,design,levels)## intercept clars foscos clar foscos Alt Baix Prim Gras
## [1,] 10.735 0.976 -0.976 0.535 -0.535 3.477 1.332 -1.619 -3.189
## [2,] 15.170 2.855 -2.855 -2.139 2.139 0.932 -2.067 -1.158 2.293
## Alegre Seriòs Nervos Tranquil mes inteligent que tu
## [1,] -0.089 0.463 3.003 -3.378 -0.686
## [2,] 1.196 3.701 0.839 -5.737 1.294
## menys inteligent que tu igual de inteligent que tu Divertit Avorrit
## [1,] 3.233 -2.547 -2.223 3.204
## [2,] 0.826 -2.119 -3.250 -0.284
## Interessant Carismatic Hippie A la Moda Provocatiu Elegante Net
## [1,] -0.293 -0.688 -3.493 -0.378 4.356 -0.485 -1.775
## [2,] 1.123 2.411 -2.292 -1.412 1.973 1.731 -2.371
## Brut
## [1,] 1.775
## [2,] 2.371With this script we generate a 25 random statges to survey 12 people of diferent ages:
#Escollim 25 escenaris amb una ordenacio diferent
# If you run this script we would have a similar result to the one below , but as it does not always produce the same , we have worked with the following
for (i in 1:25) print (names(sample(att,8,replace=F)))## [1] "personalitat" "caracter" "vestimenta" "cabell"
## [5] "ulls" "fisic" "mental" "higienePersonal"
## [1] "vestimenta" "ulls" "fisic" "caracter"
## [5] "higienePersonal" "mental" "personalitat" "cabell"
## [1] "caracter" "fisic" "vestimenta" "ulls"
## [5] "mental" "higienePersonal" "personalitat" "cabell"
## [1] "vestimenta" "ulls" "fisic" "caracter"
## [5] "higienePersonal" "cabell" "mental" "personalitat"
## [1] "vestimenta" "higienePersonal" "fisic" "caracter"
## [5] "ulls" "cabell" "mental" "personalitat"
## [1] "caracter" "personalitat" "mental" "higienePersonal"
## [5] "cabell" "fisic" "vestimenta" "ulls"
## [1] "ulls" "caracter" "cabell" "personalitat"
## [5] "fisic" "mental" "higienePersonal" "vestimenta"
## [1] "personalitat" "fisic" "mental" "ulls"
## [5] "cabell" "vestimenta" "caracter" "higienePersonal"
## [1] "cabell" "ulls" "caracter" "higienePersonal"
## [5] "fisic" "vestimenta" "personalitat" "mental"
## [1] "ulls" "caracter" "vestimenta" "fisic"
## [5] "cabell" "personalitat" "mental" "higienePersonal"
## [1] "higienePersonal" "vestimenta" "caracter" "fisic"
## [5] "ulls" "mental" "personalitat" "cabell"
## [1] "higienePersonal" "personalitat" "ulls" "fisic"
## [5] "caracter" "cabell" "vestimenta" "mental"
## [1] "fisic" "higienePersonal" "cabell" "personalitat"
## [5] "caracter" "ulls" "vestimenta" "mental"
## [1] "personalitat" "mental" "higienePersonal" "caracter"
## [5] "fisic" "cabell" "vestimenta" "ulls"
## [1] "vestimenta" "higienePersonal" "fisic" "cabell"
## [5] "mental" "ulls" "personalitat" "caracter"
## [1] "cabell" "higienePersonal" "ulls" "vestimenta"
## [5] "fisic" "caracter" "personalitat" "mental"
## [1] "cabell" "ulls" "fisic" "personalitat"
## [5] "vestimenta" "higienePersonal" "caracter" "mental"
## [1] "fisic" "mental" "higienePersonal" "cabell"
## [5] "personalitat" "caracter" "ulls" "vestimenta"
## [1] "fisic" "mental" "cabell" "vestimenta"
## [5] "higienePersonal" "caracter" "personalitat" "ulls"
## [1] "mental" "vestimenta" "caracter" "higienePersonal"
## [5] "cabell" "fisic" "ulls" "personalitat"
## [1] "caracter" "cabell" "higienePersonal" "mental"
## [5] "personalitat" "ulls" "fisic" "vestimenta"
## [1] "mental" "vestimenta" "fisic" "personalitat"
## [5] "higienePersonal" "ulls" "cabell" "caracter"
## [1] "higienePersonal" "mental" "caracter" "fisic"
## [5] "personalitat" "cabell" "ulls" "vestimenta"
## [1] "cabell" "caracter" "higienePersonal" "personalitat"
## [5] "fisic" "ulls" "mental" "vestimenta"
## [1] "caracter" "personalitat" "vestimenta" "cabell"
## [5] "higienePersonal" "fisic" "mental" "ulls"We based ou experiment with this differents statges:
1[1] “vestimenta” “personalitat” “mental” “fisic” “caracter” “cabell” “ulls” “higienePersonal”
2[1] “fisic” “ulls” “personalitat” “cabell” “mental” “caracter” “vestimenta”
[7] “higienePersonal”
3[1] “higienePersonal” “ulls” “caracter” “mental” “personalitat” “fisic”
[7] “cabell” “vestimenta”
4[1] “cabell” “ulls” “vestimenta” “fisic” “caracter” “mental” “personalitat” “higienePersonal”
5[1] “vestimenta” “caracter” “mental” “higienePersonal” “fisic” “personalitat” “cabells”
[7] “ulls”
6[1] “cabell” “ulls” “vestimenta” “mental” “caracter” “personalitat” “fisic” “higienePersonal”
7[1] “cabell” “caracter” “mental” “ulls” “personalitat” “higienePersonal”
[7] “vestimenta” “fisic”
8[1] “caracter” “ulls” “personalitat” “higienePersonal” “cabell” “fisic”
[7] “vestimenta” “mental”
9[1] “personalitat” “fisic” “mental” “vestimenta” “higienePersonal” “ulls”
[7] “cabell” “caracter”
10[1] “mental” “ulls” “fisic” “personalitat” “cabell” “caracter”
[7] “higienePersonal” “vestimenta”
11[1] “vestimenta” “ulls” “higienePersonal” “cabell” “mental” “fisic”
[7] “personalitat” “caracter”
12[1] “higienePersonal” “personalitat” “caracter” “mental” “ulls” “fisic”
[7] “cabell” “vestimenta”
13[1] “ulls” “caracter” “mental” “fisic” “vestimenta” “cabell” “personalitat” “higienePersonal”
14[1] “personalitat” “cabell” “higienePersonal” “ulls” “fisic” “mental” “caracter” “vestimenta”
15[1] “vestimenta” “mental” “cabell” “higienePersonal” “fisic” “caracter” “personalitat” “ulls”
16[1] “caracter” “personalitat” “mental” “vestimenta” “ulls” “higienePersonal” “cabell” “fisic”
17[1] “caracter” “mental” “higienePersonal” “cabell” “fisic” “personalitat” “ulls” “cabell”
18[1] “fisic” “personalitat” “cabell” “caracter” “vestimenta” “mental” “higienePersonal” “ulls”
19[1]“personalitat” “higienePersonal” “fisic” “cabell” “caracter” “mental” “vestimenta” “ulls”
20[1]“vestimenta” “caracter” “fisic” “mental” “personalitat” “cabell” “higienePersonal” “ulls”
21[1]“personalitat” “cabell” “vestimenta” “ulls” “caracter” “mental” “fisic” “higienePersonal”
22[1]“ulls” “personalitat” “fisic” “vestimenta” “caracter” “cabell” “mental” “higienePersonal”
23[1]“vestimenta” “cabell” “ulls” “higienePersonal” “fisic” “caracter” “mental” “personalitat”
24[1]“higienePersonal” “ulls” “fisic” “caracter” “vestimenta” “mental” “personalitat” “cabell”
25[1]“personalitat” “higienePersonal” “cabell” “vestimenta” “ulls” “fisic” “mental”
p1<- c(8, 1 , 6 , 2 ,15 , 22 , 9 , 24 ,18 , 13 , 3 , 16 , 5 , 20 ,23 , 11 , 7 , 4 , 21 , 10 , 14 , 19 , 12 , 25 , 17)
p2<-c(7 , 11 , 19 , 10 , 6 , 24 , 12 , 8 , 4 , 15 , 16 , 23 , 13 , 17 , 9 ,20 , 2 , 21 , 18 , 22 , 5 , 14 , 25 , 3 , 1)
p3<-c(3 ,15 ,17 ,14 , 5 , 25 ,11 ,10 ,9 ,13 ,16 ,1 ,18 ,8 ,12 ,6 ,24 ,7 ,2 ,19 ,23 ,21, 20, 22 , 4)p4 <-c(24,5,25,23,12,3,7,20,17,18,13,19,9,11,1,2,4,6,22,16,14,8,15,10,21)
p5 <-c(13,21,20,3,23,9,24,4,7,15,25,1,10,14,8,12,18,22,19,16,11,2,5,6,17)
p6 <-c(21,23,16,6,25,22,18,19,14,24,9,1,8,10,20,4,11,15,5,17,12,7,3,13,2)p7 <- c(15,4,21,11,20,2,17,24,25,19,3,1,23,8,6,12,9,13,10,14,22,5,18,16,7)
p8 <- c(11,1,20,2,6,14,25,21,7,8,15,22,10,17,12,5,9,13,18,24,23,16,3,4,19)
p9 <- c(20,15,2,7,18,19,13,12,24,25,3,22,16,14,11,10,6,8,5,1,17,21,4,9,23)p10<-c(10,6,4,20,17,5,8,7,16,1,11,9,19,24,15,18,23,22,3,2,25,13,12,21,14)
p11<-c(6,11,2,10,16,20,17,19,25,21,4,23,8,13,5,12,3,22,24,7,9,14,18,15,1)
p12<-c(15,21,8,7,4,1,20,5,2,6,23,25,13,9,24,10,18,14,12,11,19,3,17,16,22)Generate a table with the different users and choosed statges from worst to best:
y2<-cbind(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12)
y2## p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12
## [1,] 8 7 3 24 13 21 15 11 20 10 6 15
## [2,] 1 11 15 5 21 23 4 1 15 6 11 21
## [3,] 6 19 17 25 20 16 21 20 2 4 2 8
## [4,] 2 10 14 23 3 6 11 2 7 20 10 7
## [5,] 15 6 5 12 23 25 20 6 18 17 16 4
## [6,] 22 24 25 3 9 22 2 14 19 5 20 1
## [7,] 9 12 11 7 24 18 17 25 13 8 17 20
## [8,] 24 8 10 20 4 19 24 21 12 7 19 5
## [9,] 18 4 9 17 7 14 25 7 24 16 25 2
## [10,] 13 15 13 18 15 24 19 8 25 1 21 6
## [11,] 3 16 16 13 25 9 3 15 3 11 4 23
## [12,] 16 23 1 19 1 1 1 22 22 9 23 25
## [13,] 5 13 18 9 10 8 23 10 16 19 8 13
## [14,] 20 17 8 11 14 10 8 17 14 24 13 9
## [15,] 23 9 12 1 8 20 6 12 11 15 5 24
## [16,] 11 20 6 2 12 4 12 5 10 18 12 10
## [17,] 7 2 24 4 18 11 9 9 6 23 3 18
## [18,] 4 21 7 6 22 15 13 13 8 22 22 14
## [19,] 21 18 2 22 19 5 10 18 5 3 24 12
## [20,] 10 22 19 16 16 17 14 24 1 2 7 11
## [21,] 14 5 23 14 11 12 22 23 17 25 9 19
## [22,] 19 14 21 8 2 7 5 16 21 13 14 3
## [23,] 12 25 20 15 5 3 18 3 4 12 18 17
## [24,] 25 3 22 10 6 13 16 4 9 21 15 16
## [25,] 17 1 4 21 17 2 7 19 23 14 1 22Now we calculate the percentage of the best preference:
cont<-0
#now we calculate the percentage of the best preference
for (i in 1:25) {
cont<-0
if(p1[i]==25)cont=cont+1
if(p2[i]==25)cont=cont+1
if(p3[i]==25)cont=cont+1
if(p4[i]==25)cont=cont+1
if(p5[i]==25)cont=cont+1
if(p6[i]==25)cont=cont+1
if(p7[i]==25)cont=cont+1
if(p8[i]==25)cont=cont+1
if(p9[i]==25)cont=cont+1
if(p10[i]==25)cont=cont+1
if(p11[i]==25)cont=cont+1
if(p12[i]==25)cont=cont+1
if(i==1)cont1=(cont/12)*100
if(i==2)cont2=(cont/12)*100
if(i==3)cont3=(cont/12)*100
if(i==4)cont4=(cont/12)*100
if(i==5)cont5=(cont/12)*100
if(i==6)cont6=(cont/12)*100
if(i==7)cont7=(cont/12)*100
if(i==8)cont8=(cont/12)*100
if(i==9)cont9=(cont/12)*100
if(i==10)cont10=(cont/12)*100
if(i==11)cont11=(cont/12)*100
if(i==12)cont12=(cont/12)*100
if(i==13)cont13=(cont/12)*100
if(i==14)cont14=(cont/12)*100
if(i==15)cont15=(cont/12)*100
if(i==16)cont16=(cont/12)*100
if(i==17)cont17=(cont/12)*100
if(i==18)cont18=(cont/12)*100
if(i==19)cont19=(cont/12)*100
if(i==20)cont20=(cont/12)*100
if(i==21)cont21=(cont/12)*100
if(i==22)cont22=(cont/12)*100
if(i==23)cont23=(cont/12)*100
if(i==24)cont24=(cont/12)*100
if(i==25)cont25=(cont/12)*100
}cont9## [1] 16.66667Now we calculate the percentatge of the worst preference:
#now we calculate the percentage of the worst preference
for (i in 1:25) {
cont<-0
if(p1[i]==1)cont=cont+1
if(p2[i]==1)cont=cont+1
if(p3[i]==1)cont=cont+1
if(p4[i]==1)cont=cont+1
if(p5[i]==1)cont=cont+1
if(p6[i]==1)cont=cont+1
if(p7[i]==1)cont=cont+1
if(p8[i]==1)cont=cont+1
if(p9[i]==1)cont=cont+1
if(p10[i]==1)cont=cont+1
if(p11[i]==1)cont=cont+1
if(p12[i]==1)cont=cont+1
if(i==1)cont1=(cont/12)*100
if(i==2)cont2=(cont/12)*100
if(i==3)cont3=(cont/12)*100
if(i==4)cont4=(cont/12)*100
if(i==5)cont5=(cont/12)*100
if(i==6)cont6=(cont/12)*100
if(i==7)cont7=(cont/12)*100
if(i==8)cont8=(cont/12)*100
if(i==9)cont9=(cont/12)*100
if(i==10)cont10=(cont/12)*100
if(i==11)cont11=(cont/12)*100
if(i==12)cont12=(cont/12)*100
if(i==13)cont13=(cont/12)*100
if(i==14)cont14=(cont/12)*100
if(i==15)cont15=(cont/12)*100
if(i==16)cont16=(cont/12)*100
if(i==17)cont17=(cont/12)*100
if(i==18)cont18=(cont/12)*100
if(i==19)cont19=(cont/12)*100
if(i==20)cont20=(cont/12)*100
if(i==21)cont21=(cont/12)*100
if(i==22)cont22=(cont/12)*100
if(i==23)cont23=(cont/12)*100
if(i==24)cont24=(cont/12)*100
if(i==25)cont25=(cont/12)*100
}cont12## [1] 33.33333