Chapter 10 - One-sample tests of hypothesis. In this chapter, the learning objectives are: Define a hypothesis and hypothesis testing, describe the five-step hypothesis-testing procedure, distinguish between a one-tailed and a two-tailed test of hypothesis, conduct a test of hypothesis about a population mean, conduct a test of hypothesis about a population proportion, | One-Sample Tests of Hypothesis Chapter 10 GOALS Define a hypothesis and hypothesis testing. Describe the five-step hypothesis-testing procedure. Distinguish between a one-tailed and a two-tailed test of hypothesis. Conduct a test of hypothesis about a population mean. Conduct a test of hypothesis about a population proportion. Define Type I and Type II errors. Compute the probability of a Type II error. Hypothesis and Hypothesis Testing HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing. HYPOTHESIS TESTING A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. TEST STATISTIC A value, determined from sample information, used to determine whether to reject the null hypothesis. CRITICAL VALUE The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. Important Things to Remember about H0 and H1 H0: . | One-Sample Tests of Hypothesis Chapter 10 GOALS Define a hypothesis and hypothesis testing. Describe the five-step hypothesis-testing procedure. Distinguish between a one-tailed and a two-tailed test of hypothesis. Conduct a test of hypothesis about a population mean. Conduct a test of hypothesis about a population proportion. Define Type I and Type II errors. Compute the probability of a Type II error. Hypothesis and Hypothesis Testing HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing. HYPOTHESIS TESTING A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. TEST STATISTIC A value, determined from sample information, used to determine whether to reject the null hypothesis. CRITICAL VALUE The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. Important Things to Remember about H0 and H1 H0: null hypothesis and H1: alternate hypothesis H0 and H1 are mutually exclusive and collectively exhaustive H0 is always presumed to be true H1 has the burden of proof A random sample (n) is used to “reject H0” If we conclude 'do not reject H0', this does not necessarily mean that the null hypothesis is true, it only suggests that there is not sufficient evidence to reject H0; rejecting the null hypothesis then, suggests that the alternative hypothesis may be true. Equality is always part of H0 (. “=” , “≥” , “≤”). “≠” “” always part of H1 In actual practice, the status quo is set up as H0 If the claim is “boastful” the claim is set up as H1 (we apply the Missouri rule – “show me”). Remember, H1 has the burden of proof In problem solving, look for key words and convert them into symbols. Some key words include: “improved, better than, as effective as, different from, has changed, etc.” Keywords Inequality Symbol Part of: Larger (or more) than > H1 Smaller (or less) < H1 No more
