Often in statistics we’re interested in determining the p-value associated with a certain t-score that results from a hypothesis test. If this p-value is below some significance level, we can reject the null hypothesis of our hypothesis test.
To find the p-value associated with a t-score in R, we can use the pt() function, which uses the following syntax:
pt(q, df, lower.tail = TRUE)
where:
- q: The t-score
- df: The degrees of freedom
- lower.tail: If TRUE, the probability to the left of q in the t distribution is returned. If FALSE, the probability to the right is returned. Default is TRUE.
The following examples illustrate how to find the p-value associated with a t-score for a left-tailed test, right-tailed test, and a two-tailed test.
Left-tailed test
Suppose we want to find the p-value associated with a t-score of -0.77 and df = 15 in a left-tailed hypothesis test.
#find p-value pt(q=-.77, df=15, lower.tail=TRUE) [1] 0.2266283
The p-value is 0.2266. If we use a significance level of α = 0.05, we would fail to reject the null hypothesis of our hypothesis test because this p-value is not less than 0.05.
Right-tailed test
Suppose we want to find the p-value associated with a t-score of 1.87 and df = 24 in a right-tailed hypothesis test.
#find p-value pt(q=1.87, df=24, lower.tail=FALSE) [1] 0.03686533
The p-value is 0.0368. If we use a significance level of α = 0.05, we would reject the null hypothesis of our hypothesis test because this p-value is less than 0.05.
Two-tailed test
Suppose we want to find the p-value associated with a t-score of 1.24 and df = 22 in a two-tailed hypothesis test.
#find two-tailed p-value 2*pt(q=1.24, df=22, lower.tail=FALSE) [1] 0.228039
To find this two-tailed p-value we simply multiplied the one-tailed p-value by two.
The p-value is 0.2280. If we use a significance level of α = 0.05, we would fail to reject the null hypothesis of our hypothesis test because this p-value is not less than 0.05.
Related: You can also use this online T Score to P Value Calculator to find p-values.