Understanding bias is really important when making decisions based on statistics. Here are some key points to keep in mind:

• What is Bias?
  Bias happens when certain groups of people are included too much or too little in a sample.

• Methods of Sampling:

  • Random Sampling: This method gives everyone the same chance to be picked. It helps reduce bias, but there might still be some randomness involved.
  • Stratified Sampling: This method breaks the population into smaller groups (called subgroups) and samples them fairly. This way, every part of the population is represented, which helps cut down on bias.

• Effects on Data:
  When sampling is unbiased, the estimates we make about the population are more accurate. For example, a biased sample could show results that misrepresent the whole population by as much as 20%.

By understanding and reducing bias, we can trust our statistical results much more.