In general, the null hypothesis will state that the two populations being tested have no statistically significant difference. [1] X Research source The alternate hypothesis will state that there is one present.
We will call this the alpha (α) level. The typical value is 0. 05. This means that there is 95% confidence that the conclusion of this test will be valid.
These values will need to be distinct when using the equation.
These are equal to the two sample sizes, or the number of data points in each population.
We will call this the k value. On the t-distribution table below, this value is referred to as df. To calculate this value, add both of the n values together and subtract 2.
We will call these x̄1 and x̄2. This is calculated by adding all of the data points in each sample set together, then dividing by the number of data points in the set (the corresponding n value).
We will call these the S-values. This is a number that describes how much the data varies inside its own sample set. Use the following formula.
If the calculated t-statistic is greater than the critical t-value, the test concludes that there is a statistically significant difference between the two populations. Therefore, you reject the null hypothesis that there is no statistically significant difference between the two populations. In any other case, there is no statistically significant difference between the two populations. The test fails to reject the null hypothesis.
