What is the difference between sampling error and bias?

What is the difference between sampling error and bias?

Sampling error refers to the error caused by observing a sample instead of the whole population, while bias is a systematic error that leads to incorrect conclusions.

Can you give me an example of sampling error?

Sure! If you survey 100 people about their favorite ice cream flavor, but they all happen to be from the same neighborhood, that's a sampling error.

And what about bias? How does that work?

Bias occurs when the sample is not representative of the population. For instance, if you only survey people at an ice cream shop, you might get biased results.

How can we reduce sampling error and bias in research?

To reduce sampling error, increase your sample size. To minimize bias, ensure your sample is randomly selected and representative of the population.