Sampling and Sampling Distributions

In this lesson, we will learn sampling. We will understand population, sample, sampling methods, sampling bias, sampling error, sample size, sampling distribution, and the Central Limit Theorem through practical examples. ## Lesson objective In this lesson, we will learn sampling and sampling distributions. In the previous lesson, we covered probability basics. We learned probability, experiment, outcome, sample space, event, independent and dependent events, conditional probability, expected value, and risk. Now we move to one of the most important topics for inferential statistics: sampling. In real data analysis, it is often not possible to measure the whole population.