The error message explains that the cor() function requires the x argument to be numeric. Your gender column has character values. You could recode that data so that Female = 1 and Male = 2 but I do not think the correlation value would be very useful. What are you trying to accomplish?
x <- c("a", "a", "a", "a", "b", "b") y <- c(1, 1, 1, 1, 2, 2) cor(as.numeric(as.factor(x)), y)
here is the output:
glad that it works now!
that particular code runs but the cor command is still giving the same error, saying that x must be numeric
Did you convert your
character object into a
factor and then into
yes using this : df9$gender <- as.factor(df9$gender)
df9$Cognitive <- as.factor(df9$Cognitive)
Cognitive is already
numeric, indicated by the tsibble with
dbl. Then you need to convert the
factor object into
Its somewhat counterproductive to make Cognitive a factor. Factors are there to compute on character strings 'as though' they are integer representations. When you already have numbers just use them directly for computation.
Will this work? I get .16. I suspect correlation is not the right tool though. Logistic regression?
datafile0 <- data.frame(gender=c("Female", "Male", "Female","Female","Female", "Male"),
cognitive=c(4.56, 6, 5.43, 2.88, 3.55, 3))
datafile0$gender <- ifelse(datafile0$gender == "Female", 0, 1)
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i want to see whether there is a correlation between make and female when it comes to cognitive competence i also want to run a t.test but not sure whether to run paired or unpaired t test. And how do i make Female = 1 and Male = 2?
that's weird, can you show me your code please?
thank u i copied your code and ran the cor it still gives me the same error
x <- c("Female", "Female", "Female", "Female", "Male", "Male")
y <- c(1, 1, 1, 1, 2, 2)