Basic - T-Test -> Grouping Factor Must have Exactly 2 Levels

Question

I am relatively new to R. For my assignment I have to start by conducting a T-Test by looking at the effect of a politician\'s (Conservative or Labour) wealth on their real

Answer 1

are you doing this:

t.test(y~x)

when you mean to do this

t.test(y,x)

In general use the ~ then you have data like

y <- 1:10
x <- rep(letters[1:2], each = 5)

and the , when you have data like

y <- 1:5
x <- 6:10

I assume you're doing something like:

y <- 1:10
x <- rep(1,10)
t.test(y~x) #instead of t.test(y,x)

because the error suggests you have no variation in the grouping factor x

Answer 2

I was having a similar problem and did not realize given the size of my dataset that one of my y's had no values for one of my levels. I had taken a series of gene readings for two groups and one gene had readings only for group 2 and not group 1. I hadn't even noticed but for some reason this presented with the same error as what I would get if I had too many levels. The solution is to remove that y or in my case gene from my analysis and then the error is solved.

Answer 3

The differences between ~ and , is the type of statistical test you are running. ~ gives you the mean differences. This is for dependent samples (e.g. before and after). , gives you the difference in means. This is for independent samples (e.g. treatment and control). These two tests are not interchangeable.