I'm using the built-in t-test function.
Code below:
t.test(
mpg$cyl[mpg$model == "a4"],
drill_df$Time_hr[mpg$model == "malibu"],
alternative = "l",
mu = 0,
conf.level = 0.95,
)
Here is a solution. Write a function t_test
calling t.test
and then round the numbers in a lapply
loop. The return value of lapply
is a list, so class "htest"
must be assigned manually before returning to caller.
t_test <- function(..., d = 2){
tt <- t.test(...)
tt <- lapply(tt, function(x){
if(is.numeric(x)) round(x, d) else x
})
class(tt) <- "htest"
tt
}
t_test(
mpg$cyl[mpg$model == "a4"],
mpg$cyl[mpg$model == "malibu"],
alternative = "l",
mu = 0,
conf.level = 0.95,
)
# Welch Two Sample t-test
#
#data: mpg$cyl[mpg$model == "a4"] and mpg$cyl[mpg$model == "malibu"]
#t = -0.54, df = 8.63, p-value = 0.3
#alternative hypothesis: true difference in means is less than 0
#95 percent confidence interval:
# -Inf 0.83
#sample estimates:
#mean of x mean of y
# 4.86 5.20