Key PointsStatement I: Type I Error refers to the decision to reject the null hypothesis when it is incorrect. A type 1 error is also known as a false positive and occurs if an investigator rejects a null hypothesis that is actually true in the population; A type I error occurs during hypothesis testing when a null hypothesis is rejected, even though it is accurate and should not be rejected. The null hypothesis assumes no cause and effect relationship between the tested item and the stimuli applied during the test. A type I error is "false positive" leading to an incorrect rejection of the null hypothesis. Hence, this statement is not correct. Statement II: Sampling error occurs due to the violation of the principle of random sampling. A sampling error happens when the sample utilized in the study isn't representative of the full population. Sampling errors usually occur, and thus, researchers invariably calculate a margin of error during final results as a statistical practice. The principle of simple sampling is that each set of things has an identical probability of being chosen. Hence, this statement is not correct.