Stats - Biases and Sampling Methods

Convenience Sampling

Taking a sample based on what’s easiest

Simple Random Sampling (SRS)

Listing each member of a population and sampling at random

Stratified Sampling

Groups are chosen to represent characteristics, then sampled randomly

Cluster Sample

Population is divided, then one of those groups is randomly chosen

Systematic Sampling

Choose a starting point, then take every Nth subject to sample

Selection Bias

Chosen sample does not accurately reflect the population

Response Bias

Subjects do not answer accurately

Non-response Bias

Insufficient amount of responses due to circumstance

Deliberate Bias

Wording of questions influences answers, skewing data

Unintentional Bias

Questions are worded in a confusing way for the participants

Desire to Please

Participants want to answer in a way that makes them look better to the person asking a question

Asking the Uninformed

Inaccurate answers are collected because responders do not admit they do not know what is being asked

Unnecessary Complexity

Questions are too confusing for a participant to respond accurately

Ordering of Questions

Questions appear in a sequence that influences how the participant answers

Confidentiality/Anonymity

Researcher does not release or does not know information about the participants