1. SECTION 8.1 BASIC PRINCIPLES OF HYPOTHESIS TESTING Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

2. Objectives 1. Define the null and alternate hypotheses 2. State conclusions to hypothesis tests 3. Distinguish between Type I and Type II errors Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

3. Define the null and alternate hypotheses Objective 1 Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

4. Null and alternate Hypotheses A study published in the Journal of the Air and Waste Management Association reported that the mean amount of particulate matter (PM) produced by cars and light trucks in an urban setting is 35 milligrams of PM per mile of travel. Suppose that a new engine design is proposed that is intended to reduce the amount of PM in the air. There are two possible outcomes that could happen with the new engine design: either the new design will reduce the level of PM, or it will not. These possibilities are called hypotheses. One of the hypotheses is called the null hypothesis and the other is called the alternate hypothesis. Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

5. Definition and Notation Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

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9. A Hypothesis Test is Like a Trial The purpose of a hypothesis test is to determine how likely it is that the null hypothesis is true. The idea behind a hypothesis test is similar to a criminal trial. At the beginning of a trial, the defendant is assumed to be innocent. Then the evidence is presented. If the evidence strongly indicates that the defendant is guilty, we abandon the assumption of innocence and conclude the defendant is guilty. In a hypothesis test, the null hypothesis is like the defendant in a criminal trial. At the start of a hypothesis test, we assume that the null hypothesis is true. Then we look at the evidence, which comes from data that have been collected. If the data strongly indicate that the null hypothesis is false, we abandon our assumption that it is true and believe the alternate hypothesis instead. This is referred to as rejecting the null hypothesis. Assume the Null Hypothesis is True Look at Evidence Decide Whether to Reject the Null Hypothesis Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

10. State conclusions to hypothesis tests Objective 2 Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

11. Stating Conclusions H 0 : Null Hypothesis H 1 : Alternate Hypothesis H 0 : Null Hypothesis H 1 : Alternate Hypothesis Null Hypothesis “might” be true Fail to Reject H 0 Accept the Alternate Hypothesis Reject H 0 Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

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14. Distinguish between Type I and Type II errors Objective 3 Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

15. Type I and Type II Errors DecisionH 0 is TrueH 0 is False Reject H 0 Type I ErrorCorrect Decision Fail to Reject H 0 Correct DecisionType II Error Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

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19. Do You Know… How to write the null and alternate hypotheses? How to determine whether a hypothesis test is left-tailed, right-tailed, or two-tailed? How to state the conclusion to a hypothesis test? How to distinguish between Type I and Type II errors and correct decisions? Copyright ©2014 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.