Descriptive, Inferential, and Multivariate Statistics

Type I and Type II Errors
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Institution
Type I and Type II Errors
The type I error is identified when the investigator decides to reject the null hypothesis (H0) from the sample evidence, yet the null hypothesis (H0) is true in the population (Brase & Brase, 2012). The type II error is noted when the findings from the research sample show that the null hypothesis (H0) is true when in actual sense the H0 is false in the population. The researchers usually decide to accept or reject the null hypothesis depending on the level of evidence that has been obtained from the sample population. For instance, a researcher may fail to reject H0 when the evidence from the sample data is not enough to justify the rejection of the null hypothesis, and therefore, the investigator will retail H0 with an understanding that the evidence did not prove beyond all doubts to be false.
The type I ...