Question

what are the differences between:

1. one sample z-test

2. one sample t-test

3. independent sample t-test

4. dependent sample t-test

5. what type of information comes from a known population vs. your sample data

Answer 1

One sample z test vs t test: Both z and t test are used to find out how the means of two data-sets differ from each-other.

The t test is based on student's t distribution while the z test is based on Normal distribution

T test is used when the population variance is unknown and Z test when it's known.

T test is used hwn the sample size is small , n<30 and z test when sample size is large, z>30.

Independent vs Dependent sample t test: The dependent t test is used when there are 2 related data sets suppose derived from the same population, to chek if there is any statistical difference in their means.Also known as paired sample t test

The independent t test is used when there are 2 data sets which are completely unrelated or derived from 2 population sets which are independent, to check the difference in their means.

3. Information from a known population vs. your sample data:

Population data sets is the entire data set. it includes all the data poits. Where as, sample data sets are just randomly selected data from the population data set. It has less number of data points.

Population Information is considered true while sample information may or may not give the true picture of the population.