Beginners Guide to Independent T-Test

The independent t-test, also known as the two-sample t-test, student’s t-test, independent sample t-test, is used to compare the mean values from two sets of samples and analyze whether it is significant that the samples from two populations have different mean values.

In simple terms, if you take two samples from the same population, it is quite suspected that the means of both the samples are possibly identical. On the contrary, if you take two samples from a different population having different mean values, it is more likely that the twp samples might have a difference. Here, under such assumptions, the independent t-test method can help you find out whether there is a significant difference between the means of two unrelated of separate populations.

Condition for independent t-test:

To conduct an independent t-test on an online calculator or in general, you need to follow below-given conditions:

• There should be one independent, categorical variable that has two groups, eg. Gender is a categorical variable that has two groups, male and female, where an individual of one group cannot be the part of other groups.
• One continuous dependent variable, eg. Height, age, or weight can be one continuous variable for both the male and female gender.

Example for independent t-test:

A study is conducted to find the effect of alcohol on liver functioning, taking 20 volunteers (ten males and ten females) from a group of 150 males and females. The randomly selected individual from both groups is tested for their liver metabolic activity for ten respective days on consuming alcohol.

Suppose, from the available data; you wish to find out whether alcohol consumption has a more significant effect on male liver functioning or female liver functioning?

Say, on calculating values from each group, the mean for the male group is 120, whereas the mean for the female group is 100. From the obtain data mean you might assume that the male liver is more likely to get affected by alcohol consumption then females by observing the significant difference of 20 between the values.

However, here, the question arises does the difference between the two means is simply a chance due to sampling variation, or does the data provide the evidence of a significant difference in alcohol consumption on the male and female liver. On applying a null hypothesis/alternative hypothesis on the independent t-test calculator, you can find out the reliable results.