Type I errors (also known as a "false positive") occur when a test erroneously rejects a true null hypothesis. In other words, the test incorrectly concludes that the observed effect is significant or real when, in fact, it is not.
A type I error is a statistical mistake where the null hypothesis is rejected, despite it being true. This is also known as a false positive. This means that the test concluded that the observed effect was significant when in reality, it was not. Type I errors are more likely to occur when the sample size is small or when too many tests are conducted at once. To avoid type I errors, it is important to use an appropriate sample size and to consider the power of the test before conducting it.
Learn more about error here
https://brainly.com/question/13370015
#SPJ4
