Sampling Bias

Bias makes our data inaccurate. We try to minimize or eliminate bias from sampling because we want the most accurate data possible. The three types of bias that we can find are:

1. Selection Bias: this is when we exclude a group (either on purpose or by accident) from having a chance to participate in the sample.

2. Measurement/Response Bias: when we have errors in the way our responses are measured. This could be from math mistakes, from people responding with the wrong answers, or from rounding error.

3. Nonresponse Bias: when people don't respond to a question because they 1) don't know the answer 2) don't feel like writing an answer or 3) may feel pressured or embarrassed to give an answer.