Reputation: 45
Below is my dataset
dput(ex0112)
Dataset:
structure(list(BP = c(8L, 12L, 10L, 14L, 2L, 0L, 0L, -6L, 0L,
1L, 2L, -3L, -4L, 2L), Diet = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("FishOil", "RegularOil"
), class = "factor")), class = "data.frame", row.names = c(NA,
-14L))
To find the t-statistic for entire (column BP) I have achieved it using the below R code.
library(Sleuth3)
t.test(BP~Diet, data=ex0112)
But how do I calculate For the hypothesis that mu is zero and construct the t -statistic for (column BP) for only Regular Oil Diet and also how to Find the two-sided p-value as the proportion of values from a t-distribution farther from 0 than this value using R?
Upvotes: 0
Views: 606
Reputation: 39585
I would suggest next approach. You can use one variable in t.test()
which has the options for mu
parameter and the two-sided
alternative you want. Here the code using your dput()
data as df
:
#Test
test <- t.test(df$BP[df$Diet=='RegularOil'], mu = 0, alternative = "two.sided")
test
#Extract p-value
test$p.value
Output:
One Sample t-test
data: df$BP[df$Diet == "RegularOil"]
t = -0.94943, df = 6, p-value = 0.3791
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
-4.088292 1.802578
sample estimates:
mean of x
-1.142857
And p-val:
[1] 0.3790617
Upvotes: 1