Calculate Critical t-Value in R (3 Examples)


In this article, I’ll illustrate how to calculate critical t-values in R.

Table of contents:

So without further additions, let’s dive right into the examples.


Example 1: Calculate Critical t-Value of One-Tailed t-Test

The following R programming code illustrates how to compute the critical t-values for a one-sided t-test.

In this example, we are using a confidence level of 0.05 with five degrees of freedom.

For this, we can apply the abs and qt functions as shown below:

abs(qt(p = 0.05, df = 5))                                  # 95% confidence, 5 DF, one-sided
# [1] 2.015048

The RStudio console returns the result: Student’s t critical value for a one-sided confidence interval with p = 0.05 and df = 5 is 2.015048.


Example 2: Calculate Critical t-Value of Two-Tailed t-Test

This example illustrates how to compute critical values for a two-sided t-test.

For this, we simply have to divide our confidence level by 2 within the qt function (i.e. p = 0.05 / 2):

abs(qt(p = 0.05 / 2, df = 5))                              # 95% confidence, 5 DF, two-sided
# [1] 2.570582

In this case, the critical value is 2.570582.


Example 3: Create Matrix of Critical t-Values

In case you want to look up a larger amount of t-statistic values for different confidence levels and degrees of freedom, you may create your own table of critical t-values.

First, we have to specify the confidence levels that we want to calculate:

conf_levels <- c(0.0001, 0.001, 0.01, 0.05, 0.1)           # Vector of confidence levels

Next, we can create a table where each column corresponds to different degrees of freedom:

data_t <- round(data.frame(DF1 = abs(qt(p = conf_levels, df = 1)),  # Create data.frame
                           DF2 = abs(qt(p = conf_levels, df = 2)),
                           DF3 = abs(qt(p = conf_levels, df = 3)),
                           DF4 = abs(qt(p = conf_levels, df = 4)),
                           DF5 = abs(qt(p = conf_levels, df = 5)),
                           DF10 = abs(qt(p = conf_levels, df = 10)),
                           DF25 = abs(qt(p = conf_levels, df = 25)),
                           DF50 = abs(qt(p = conf_levels, df = 50))), 2)
rownames(data_t) <- conf_levels

Finally, we can print our matrix of critical Student’s t values:

data_t                                                     # Print data frame


table 1 data frame critical t value


Video, Further Resources & Summary

I have recently published a video on my YouTube channel, which explains the contents of this tutorial. You can find the video below.


The YouTube video will be added soon.


In addition, you might have a look at the other tutorials which I have published on my website. A selection of interesting articles about statistics in R can be found below:


Summary: In this article, I have illustrated how to find critical t-statistic values in the R programming language. In case you have additional questions, tell me about it in the comments section below.


Subscribe to my free statistics newsletter

Get regular updates on the latest tutorials, offers & news at Statistics Globe.
I hate spam & you may opt out anytime: Privacy Policy.

Leave a Reply

Your email address will not be published. Required fields are marked *

Fill out this field
Fill out this field
Please enter a valid email address.