Type I error?

A Type I error, also known as a false positive, occurs when a null hypothesis that is actually true is incorrectly rejected. This means that the test results suggest that there is a significant effect or relationship when in reality there is not. This type of error is typically denoted by the symbol α (alpha) and is the probability of rejecting a true null hypothesis.

A Type I error, also known as a false positive, occurs when a hypothesis test incorrectly rejects the null hypothesis when it is actually true. In other words, the test concludes that there is a significant difference or relationship between variables when there is actually none.

Consequences of a Type I Error:

- Falsely declaring a significant effect or relationship
- Wasting resources and time on further research or actions based on the erroneous result
- Reducing confidence in research findings
- Undermining the scientific credibility of the researcher or study