I developed an excel template that calculates independent two sample t test. It also writes summary report which is based on p-value. This spreadsheet can handle up to 10,000 cases.

The independent t test allows researchers to evaluate the mean difference between two populations using the data from two separate samples.

The general purpose of the independent t test is to determine whether the sample mean difference obtained is a real difference between the two populations or simply the result of sampling error.

Check the p-value. It is the lowest level of significance at which we can reject our null hypothesis. It helps researchers determine if their hypotheses are correct.

Suppose the p-value is 0.39, i.e. greater than 0.05 (or 5 percent), it can be concluded that we don't reject the null hypothesis at 5% significance level. That implies there is no mean difference between the two groups.

Suppose the p-value is 0.029, i.e. less than 0.05 (or 5 percent), it can be concluded that we reject the null hypothesis at 5% significance level. That implies there is a mean difference between the two groups.

**Download link : Independent t-test**

**Meaning :**

The independent t test allows researchers to evaluate the mean difference between two populations using the data from two separate samples.

**Purpose :**

The general purpose of the independent t test is to determine whether the sample mean difference obtained is a real difference between the two populations or simply the result of sampling error.

**Examples :**

- Do males and females differ in terms of their exam scores?

- Is diet A better than diet B for asthma patients?

**Assumptions :**

- The two groups must be independent.
- The scores in each population must be normally distributed.
- The two populations must have equal variances.

Suppose the p-value is 0.39, i.e. greater than 0.05 (or 5 percent), it can be concluded that we don't reject the null hypothesis at 5% significance level. That implies there is no mean difference between the two groups.

Suppose the p-value is 0.029, i.e. less than 0.05 (or 5 percent), it can be concluded that we reject the null hypothesis at 5% significance level. That implies there is a mean difference between the two groups.

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