Code: Alles auswählen
data.csv <- read.csv2("henderson_replication_data1.csv", na = "NA")
install.packages(pwr)
library(pwr)
pwr.anova.test(k=3, f=0.25, sig.level=0.05, power=0.95)
pwr.anova.test(k=3, n=139, f=0.25, sig.level=0.05)
pwr.anova.test(k=3, n=29.33333333333, f=0.25, sig.level=0.05)
StrongMixed <- "3 3 1 -2 2 1 2 -1 2 -3 2 -1 -1 0 0 0 2 -2 2 0 1 -2 1 1 3 0 0 2 -1 1 -1 0 1 1 3 -1 -3 -3 -1 3 0 -1 -2 -1 -1 1 -1 -3 -1 3 1 2 2 1 -3 3 0 2 0 2 2 3 1 0 1 0 -1 2 2 1 -2 -1 -1 1 -2 2 3 0 1 0 -2 3 1 2 -2 -2 2 3"
NotTorn <- "-3 3 -2 2 2 3 2 -2 2 3 1 -1 -1 -1 0 -2 2 -2 2 2 2 1 3 -1 -1 -2 -2 -3 0 1 -1 2 3 1 1 -2 -3 3 -1 -3 -2 -2 -2 -2 -1 1 -1 -3 -1 0 3 2 2 -1 -3 0 2 1 -1 -1 -2 1 1 -2 -2 -1 1 1 -2 2 -3 -1 -1 2 -3 2 0 -1 2 0 -3 -3 -2 -2 -3 -2 -3 3"
Indecisive <- "-3 3 -1 -3 1 1 1 1 1 -1 1 0 -1 -1 0 -2 3 -2 2 2 1 0 1 2 -3 2 -2 -3 0 1 -1 2 1 NA 2 1 -3 -1 0 -3 -2 -2 -2 -2 -1 NA -1 -3 -2 -2 1 1 1 0 -3 -2 2 1 -1 -1 3 1 -1 -2 -1 -1 0 1 -3 1 -2 0 0 -1 -2 1 -2 1 -1 1 -2 -3 -1 -3 -2 -2 -3 3"
Einstellung <- data.frame(
StrongMixed=as.numeric(strsplit(StrongMixed, " ")[[1]]),
NotTorn=as.numeric(strsplit(NotTorn, " ")[[1]]),
Indecisive=as.numeric(strsplit(Indecisive, " ")[[1]]))
Einstellung$new <- rowMeans(mscstart, na.rm=TRUE)
Einstellung
data.csv $Gender <- factor (data.csv $Gender, labels=c ( "male" , "female" ))
dataf <-dplyr :: filter (data.csv,Gender == "female" )
datam <-dplyr :: filter (data.csv,Gender == "male" )
boxplot (data.csv $Age ~ data.csv $Gender, main= "Alterstruktur der Geschlechter in der Stichprobe" , xlab= "Geschlecht" , ylab= "Alter in Jahren" , col=c ( "blue" , "red" ))
boxplot (data.csv $Age ~ data.csv $Gender, plot= "F" )
table (data.csv $Gender,data.csv $Age)
hist (dataf$Age, plot= "F" )
hist (datam $Age, plot= "F")
data.csv$Age1 <- cut(data.csv$Age,breaks=c(18,22,24,26,30)
agesummary <- table(data.csv$Gender,data.csv$Age1)
chisq.test(table(data.csv$Gender,data.csv$Age1))
Code: Alles auswählen
data.csv$Age1 <- cut(data.csv$Age,breaks=c(18,22,24,26,30)
agesummary <- table(data.csv$Gender,data.csv$Age1)
chisq.test(table(data.csv$Gender,data.csv$Age1))
Code: Alles auswählen
> data.csv$Age1 <- cut(data.csv$Age,breaks=c(18,22,24,26,30)
+ agesummary <- table(data.csv$Gender,data.csv$Age1)
Fehler: unerwartetes Symbol in:
"data.csv$Age1 <- cut(data.csv$Age,breaks=c(18,22,24,26,30)
agesummary"
> agesummary <- table(data.csv$Gender,data.csv$Age1)
Fehler in table(data.csv$Gender, data.csv$Age1) :
alle Argumente müssen die selbe Länge haben
> chisq.test(agesummary)
Fehler in is.data.frame(x) : Objekt 'agesummary' nicht gefunden
Code: Alles auswählen
> chisq.test(agesummary)
Pearson's Chi-squared test
data: agesummary
X-squared = NaN, df = 3, p-value = NA