Whenever data is collected, there is a risk that the sample is biased. Here are some potential types of bias.
Types of Bias
- Non-Response Bias
- When a large percentage of those sampled do not respond or participate.
- Response Bias
- When study participants either do not respond truthfully or give answers they feel the researcher wants to hear. For example, when students are asked if they ever cheated on an exam even those who have would respond with "no."
- This bias occurs when the sample selected does not reflect the population of interest. For instance, you are interested in the attitude of female students regarding campus safety but when sampling you also include males. In this case, your population of interest was female students however your sample included subjects not in that population (i.e. males).
Students interested in pursuing topics related to the design of experiments might explore STAT 503: Design of Experiments. STAT 503 includes extensive coverage implementation and analysis of a wide range of experimental designs.