#Degrees of freedom for ta2 calculator how to#

H A: μ 1 ≠ μ 2 (the two population means are not equal)įirst, we will calculate the pooled standard deviation s p:.H 0: μ 1 = μ 2 (the two population means are equal).We will perform a two sample t-test with the following hypotheses:

Suppose we collect a random sample of turtles from each population with the following information: Suppose we want to know whether or not the mean weight between two different species of turtles is equal. Example 2: Degrees of Freedom for Two Sample t-test We have sufficient evidence to say that the mean weight of this species of turtle is not equal to 310 pounds. Since this p-value is less than our significance level α = 0.05, we reject the null hypothesis. Lastly, we’ll plug in the test statistic and degrees of freedom into the T Score to P Value Calculator to find that the p-value is 0.00149. Next, we’ll calculate the degrees of freedom:

H A: μ ≠ 310 (population mean is not equal to 310 pounds)įirst, we’ll calculate the test statistic:.

H 0: μ = 310 (population mean is equal to 310 pounds).

We will perform a one sample t-test with the following hypotheses: Suppose we collect a random sample of turtles with the following information: Suppose we want to know whether or not the mean weight of a certain species of turtle is equal to 310 pounds. Example 1: Degrees of Freedom for One Sample t-test

#Degrees of freedom for ta2 calculator how to#

The following examples show how to calculate the degrees of freedom for each type of t-test in practice. Paired Samples t-test: n-1 where n is the total number of pairs.

Two Sample t-test: df = n 1 + n 2 – 2 where n 1, n 2 are the total observations from each sample.

One Sample t-test: df = n-1 where n is the total number of observations. Here is how to calculate the degrees of freedom for each type of test: When performing each t-test, you’ll have to calculate a test statistic and a corresponding degrees of freedom. Paired Samples t-test: Used to compare two population means when each observation in one sample can be paired with an observation in the other sample. Two Sample t-test: Used to compare two population means. One Sample t-test: Used to compare a population mean to some value. In statistics, there are three commonly used t-tests: