How to Read the t-Distribution Table - Statology (2024)

This tutorial explains how to read and interpret the t-Distribution table.

What is the t-Distribution Table?

The t-distribution tableis a table that shows the critical values of the t distribution. To use the t-distribution table, you only need to know three values:

  • The degrees of freedom of the t-test
  • The number of tails of the t-test (one-tailed or two-tailed)
  • The alpha level of the t-test (common choices are 0.01, 0.05, and 0.10)

Here is an example of the t-Distribution table, with the degrees of freedom listed along the left side of the table and the alpha levels listed along the top of the table:

How to Read the t-Distribution Table - Statology (1)

When you conduct a t-test, you can compare the test statistic from the t-test to the critical value from the t-Distribution table. If the test statistic is greater than the critical value found in the table, then you can reject the null hypothesis of the t-test and conclude that the results of the test are statistically significant.

Let’s walk through some examples of how to use the t-Distribution table.

Examples of How to Use the t-Distribution Table

The following examples explain how to use the t-Distribution table in several different scenarios.

Example #1: One-tailed t-test for a mean

A researcher recruits 20 subjects for a study and conducts a one-tailed t-test for a mean using an alpha level of 0.05.

Question: Once she conducts her one-tailed t-test and obtains a test statistic t, what critical value should she comparetto?

Answer: For a t-test with one sample, the degrees of freedom is equal ton-1, which is 20-1 = 19 in this case.The problem also tells us that she is conducting a one-tailed test and that she is using an alpha level of 0.05, so the corresponding critical value in the t-distribution table is1.729.

Example #2: Two-tailed t-test for a mean

A researcher recruits 18 subjects for a study and conducts a two-tailed t-test for a mean using an alpha level of 0.10.

Question: Once she conducts her two-tailed t-test and obtains a test statistic t, what critical value should she comparetto?

Answer: For a t-test with one sample, the degrees of freedom is equal ton-1, which is 18-1 = 17 in this case.The problem also tells us that she is conducting a two-tailed test and that she is using an alpha level of 0.10, so the corresponding critical value in the t-distribution table is1.74.

Example #3: Determining the critical value

A researcher conducts a two-tailed t-test for a mean using a sample size of 14 and an alpha level of 0.05.

Question: What would the absolute value of her test statistictneed to be in order for her to reject the null hypothesis?

Answer: For a t-test with one sample, the degrees of freedom is equal ton-1, which is 14-1 = 13 in this case.The problem also tells us that she is conducting a two-tailed test and that she is using an alpha level of 0.05, so the corresponding critical value in the t-distribution table is2.16.This means that she can reject the null hypothesis if the test statistictis less than -2.16 or greater than 2.16.

Example #4: Comparing a critical value to a test statistic

A researcher conducts a right-tailed t-test for a mean using a sample size of 19 and an alpha level of 0.10.

Question: The test statistic tturns out to be 1.48. Can shereject the null hypothesis?

Answer: For a t-test with one sample, the degrees of freedom is equal ton-1, which is 19-1 = 18 in this case.The problem also tells us that she is conducting a right-tailed test (which is a one-tailed test) and that she is using an alpha level of 0.10, so the corresponding critical value in the t-distribution table is1.33. Since her test statistictis greater than 1.33, she can reject the null hypothesis.

Should You Use the t Table or the z Table?

One problem that students frequently encounter is determining if they should use the t-distribution table or the z table to find the critical values for a particular problem. If you’re stuck on this decision, you can use the following flow chart to determine which table you should use:

How to Read the t-Distribution Table - Statology (2)

Additional Resources

For a complete list of critical value tables, including a binomial distribution table, a chi-square distribution table, a z-table, and more, check out this page.

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FAQs

How do you read a table t-distribution? ›

How to use a t-table
  1. Identify if the table is for two-tailed or one-tailed tests. Then, decide if you have a one-tailed or a two-tailed test. ...
  2. Identify the degrees of freedom for your data. ...
  3. Find the cell in the table at the intersection of your α level and degrees of freedom.

How do you read t in statistics? ›

Higher values of the t-score indicate that a large difference exists between the two sample sets. The smaller the t-value, the more similarity exists between the two sample sets.

How do you read a critical t-value table? ›

How to Use the Table:
  1. Find your degrees of freedom in the df column and use that row. to find the next smaller number.
  2. Read the probability in the top row. ...
  3. If your t is to the right of all numbers, then P < 0.0005 (good!)
  4. Remember that P < 0.05 is the arbitrary value that is generally accepted to be significant.

What is the meaning of t-distribution table? ›

What is the t-Distribution Table? The t-distribution table is a table that shows the critical values of the t distribution. To use the t-distribution table, you only need to know three values: The degrees of freedom of the t-test. The number of tails of the t-test (one-tailed or two-tailed)

How do you explain t distribution? ›

The t-distribution is a way of describing a set of observations where most observations fall close to the mean, and the rest of the observations make up the tails on either side. It is a type of normal distribution used for smaller sample sizes, where the variance in the data is unknown.

How do you interpret the t-score in statistics? ›

T-scores indicate how many standard deviation units an examinee's score is above or below the mean. TScores always have a mean of 50 and a standard deviation of 10, so any T-Score is directly interpretable. A TScore of 50 indicates a raw score equal to the mean.

How to report t-test results in a table? ›

When reporting the result of an independent t-test, you need to include the t-statistic value, the degrees of freedom (df) and the significance value of the test (p-value). The format of the test result is: t(df) = t-statistic, p = significance value.

How do you interpret t stat and p-value? ›

The t-statistic is also used to calculate the p-value, which represents the probability of observing the observed difference (or a more extreme difference) by chance alone. If the p-value is below a certain threshold (often 0.05), it suggests that the observed difference is statistically significant.

How do you interpret critical value and t-value? ›

If the absolute value of the t-value is greater than the critical value, you reject the null hypothesis. If the absolute value of the t-value is less than the critical value, you fail to reject the null hypothesis.

How to read a T table for confidence intervals? ›

Find the critical value of t in the two-tailed t table. Multiply the critical value of t by s/√n. Add this value to the mean to calculate the upper limit of the confidence interval, and subtract this value from the mean to calculate the lower limit.

How to read t-test results? ›

To interpret the t-test results, all you need to find on the output is the p-value for the test. To do an hypothesis test at a specific alpha (significance) level, just compare the p-value on the output (labeled as a “Sig.” value on the SPSS output) to the chosen alpha level.

How to read a statistics table? ›

To read a statistical table, look at the title, then look at the headings. Using the categories at the top and left side of the table, read across a row and down a column to locate specific information.

What is the T * at the 0.05 significance level? ›

As an example if your level of significance is 0.05, the correspondent t-stat value is 1.96, thus when the t-stat reported in the output is higher than 1.96 you reject the null hypothesis and your coefficient is significant at 5% significance level.

How do you read a transition table? ›

The first row of the transition table can be read as, when the current state is q0, on input 0 the next state will be q0 and on input 1 the next state will be q1. In the second row, when the current state is q1, on input 0 the next state will be either q1 or q2, and on 1 input the next state will be q2.

References

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