Post provided by REBECCA FISHER and GLENN R SHIELL
As environmental managers, we’re frequently asked to make judgements about the relative health of the environment. This is often difficult because, by its nature, the environment is highly variable in space and time. Ideally, such judgements should be informed by robust scientific investigation, or more precisely, the reliable interpretation of the resulting data.
Type I and Type II Errors
Even with robust investigations and good data, our interpretations can sometimes be wrong. In general, this happens when:
- the investigation concludes that an impact has occurred, when in fact it hasn’t (Type I error)
- fails to detect an impact, when an impact has actually occurred (Type II error).
Understanding the circumstances that lead to these errors is unfortunately complicated, and difficult unless you have a strong statistical background. Continue reading