Understand Statistical Sampling Without the Maths Degree

A survey of two thousand people says seven in ten adults feel anxious. You have no idea if that means anything. This explains how sampling actually works, why convenience sampling produces garbage results, what sample size genuinely affects, and three questions to ask before you let a cited statistic change your mind about anything.

Explain how statistical sampling works for someone with no statistics background. Cover:
1. Why you cannot just ask everyone: what sampling is and when it is necessary
2. The difference between random sampling, stratified sampling, and convenience sampling, with a concrete example of each
3. What sample size actually affects and a rough guide to how large a sample needs to be for a given claim to hold
4. Why polls and surveys are often misleading: three structural problems beyond just sample size
5. How to read a claim that cites a study: three questions to ask before trusting the number

Use everyday examples rather than abstract statistics. No equations.