david wants to complete a hypothesis test with the least amount of probability for error. if he sets the…

david wants to complete a hypothesis test with the least amount of probability for error. if he sets the significance level to 1%, assuming his sample is truly random, what else could he adjust in the test in order to reduce error? he could change the population mean. he could increase the sample size. he could change the population standard deviation. he could decrease the sample size.

david wants to complete a hypothesis test with the least amount of probability for error. if he sets the significance level to 1%, assuming his sample is truly random, what else could he adjust in the test in order to reduce error? he could change the population mean. he could increase the sample size. he could change the population standard deviation. he could decrease the sample size.

Answer

Brief Explanations:

In hypothesis - testing, increasing the sample size reduces the standard error of the sample statistic. A smaller standard error leads to more accurate estimates and reduces the probability of both Type - I and Type - II errors. The population mean and standard deviation are parameters of the population and are not under the control of the researcher in the context of adjusting a hypothesis test. Decreasing the sample size would increase the standard error and the probability of error.

Answer:

He could increase the sample size.