Introduction
At its heart, the goal of an epidemiologic study is to measure a disease frequency or to compare disease frequency in two or more exposure groups in order to measure the extent to which there is an association. There are three primary challenges to achieving an accurate estimate of the association:
- Bias
- Confounding, and
- Random error.
Random error occurs because the estimates we produce are based on samples, and samples may not accurately reflect what is really going on in the population at large. .
There are differences of opinion among various disciplines regarding how to conceptualize and evaluate random error. In this module the focus will be on evaluating the precision of the estimates obtained from samples.
Learning Objectives
After successfully completing this unit, the student will be able to:
- Explain the effects of sample size on the precision of an estimate
- Define and interpret 95% confidence intervals for measures of frequency and measures of association
- Define and interpret p-values
- Discuss common mistakes in the interpretation of measures of random error
