The assignment should be uploaded or wriitten in the ajou bb technology.
data file efa.csv: The data set contains what customers consider while purchasing car. The survey questions were framed using 5-point likert scale with 1 being very low and 5 being very high. The variables were the following:
Price
Safety
Exterior looks
Space and comfort
Technology
After sales service
Resale value
Fuel type
Fuel efficiency
Color
Maintenance
Test drive
Product reviews
Testimonials
In order to perform the factor analysis in r, you would need to install the following packages: psych
and GPArotation
. Do the following codes.
install.packages('psych') install.packages('GPArotation')
Assignment
Do the following tasks with your group members
efa <- read.csv("http://commres.net/wiki/_media/efa.csv")
# use str(), head() function
?fa.parallel
fa.parallel
with following options (수업에서 다루지 않았읍니다. help 문서를 보고 완성하세요)fm = minres
fa = fa
# 아래를 먼저 수행해서 패키지를 탑재한 후에 fa 분석을 해야 합니다 library(psych) library(GPAroation) # 그 후에 something like the below fa.parallel(cor(efa), fm="minres", fa="fa", n.obs = nrow(efa))
efa.fa.ini <- fa(efa)
names(efa.fa.ini)
and answer the below questions# 수업시간에 아래 명령어를 출력해서 보면 efa.fa.ini 가 분석한 결과값이 컬럼별로 어떻게 # 저장되어 있는지 볼 수 있다고 했습니다. names(efa.fa.ini) # 각 컬럼을 보기 위해서는 efa.fa.ini$n.obs와 같이 확인한다 했습니다
efa.fa.3 <- fa(options~)
# 다음을 이용하여 명령어를 완성하여 분석 # efa.fa.3 <- fa(efa, nfactor = 3, . . . . ) efa.fa.3 <- fa(efa, nfactors = 3, rotate = "varimax", fm="minres")
# print efa.fa.3
temp <- data.frame(efa.fa.ini$communality, efa.fa.3$communality)
print(fa.sort(efa.fa.3$loadings), cutoff = 0.3)
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