An Intuitive Guide To Various Statistical Tests
In my previous blog, I covered some of the basics of hypothesis testing. The idea for the blog was to introduce learners to hypothesis testing and present some of the intricacies in an intuitive fashion.
Now that we know what hypothesis testing and some auxiliary terms are, Let us get versed with some of the statistical tests as well.
I shall be covering a few of these statistical tests mentioned above. To get started with, let's start with the Z/T- test
T-Test
T-tests are a statistical way of testing a hypothesis when:
•We do not know the population variance
•Our sample size is small, n < 30
On the other hand, we resort to the z- test when our sample size is large and when the population variance is known. If the sample size is large enough, then the Z test and T-Test will conclude with the same results. For a large sample size, Sample Variance will be a better estimate of Population variance so even if population variance is unknown, we can use the Z test using sample variance.
