T-tests are best performed when the data consists of a small sample size, i.e., less than 30. T-tests assume the standard deviation is unknown, while Z-tests assume it is known.

Central Limit Theorem, or CLT, is a statistical theory stating that as the size of a sample grows, the results tend to approximate a normal distribution of results. Read more here.

On watching this video, students should be able to: Explain why the normal distribution is so important for statistics. Explain that the central limit theorem (CLT) is about the distribution of point ...

License: CC0. The Central Limit Theorem for proportions: Central Limit Theorem for Proportions This Shiny app allows users to drag sliders to change the population proportion, sample size and number ...

“The claim of the Central Limit Theorem is that as you let the size of that sum get bigger and bigger, then the distribution of that sum, how likely it is to fall into different possible values ...