Sources of Variation

Example: How many text messages on an average a 19-year-old sends in a day.

1. Natural variation: Not all students will send the same number of text messages in a day. Taking one sample will not give all the information we need.
2. Explainable variation: Are there any other reasons why asking one student will not give the average for all 19 years? There are different types of students. Girls seem to send more texts and maybe rich students send more tickets. This is explainable variation.
3. Sampling error: I take a sample of 5 students. You take a sample of 5 students. Do you think the same mean/average will be the same? We will likely not, because we will choose different people. There are infinite different samples we can take from a population. Sampling error exists because a sample is not a true representative of the entire population. Sample size matters; the larger the sample size greater is the confidence.
4. Biased sampling: Bias happens when you pick up your samples based on prejudices like not including poor students in the above example.