© 2001 Prentice-Hall, Inc.Chap 9-1 BA 201 Lecture 14 Fundamentals of Hypothesis Testing

© 2001 Prentice-Hall, Inc. Chap 9-2 Topics Hypothesis Testing Methodology

© 2001 Prentice-Hall, Inc. Chap 9-3 Result Probabilities H 0 : Innocent The Truth Verdict InnocentGuilty Decision H 0 TrueH 0 False Innocent CorrectError Do Not Reject H  Type II Error (  ) Guilty Error Correct Reject H 0 Type I Error (  ) Power (1 -  ) Jury Trial Hypothesis Test H 1 : Guilty

© 2001 Prentice-Hall, Inc. Chap 9-4 What is a Hypothesis? A Hypothesis is a Claim (Assumption) about the Population Parameter Examples of parameters are population mean or proportion The parameter must be identified before analysis I claim the mean GPA of this class is 3.5! © T/Maker Co.

© 2001 Prentice-Hall, Inc. Chap 9-5 The Null Hypothesis, H 0 States the Assumption (Numerical) to be Tested E.g. The average #TV sets in the U.S. homes is at least 3 ( ) Null Hypothesis is Always about a Population Parameter ( ), Not about a Sample Statistic ( )

© 2001 Prentice-Hall, Inc. Chap 9-6 The Null Hypothesis, H 0 Begin with the Assumption that the Null Hypothesis is True Similar to the notion of innocent until proven guilty Refer to the Status Quo Always Contains the “=” Sign The Null Hypothesis May or May Not be Rejected The Null Hypothesis Can Never be Proved nor Shown to be True (continued)

© 2001 Prentice-Hall, Inc. Chap 9-7 The Alternative Hypothesis, H 1 Is the Opposite of the Null Hypothesis E.g. The average #TV sets in the U.S. homes is less than 3 ( ) Challenges the Status Quo Never Contains the “=” Sign The Alternative Hypothesis May or May Not be Accepted Is Generally the Hypothesis that is Believed (or Needed to be Showed) to be True by the Researcher

© 2001 Prentice-Hall, Inc. Chap 9-8 Error in Making Decisions Type I Error Reject a true null hypothesis When the null hypothesis is rejected, we can say that “We have shown the null hypothesis to be false (with some ‘slight’ probability of making a wrong decision) Has serious consequences Probability of Type I Error is Called level of significance Set by researcher Type II Error Fail to Reject a false null hypothesis Probability of Type II Error is The Power of the test is

© 2001 Prentice-Hall, Inc. Chap 9-9 Error in Making Decisions Probability of Not Making Type I Error Called the Confidence Coefficient (continued)

© 2001 Prentice-Hall, Inc. Chap 9-10 Type I & II Errors Have an Inverse Relationship   Reduce probability of one error and the other one goes up holding everything else unchanged.

© 2001 Prentice-Hall, Inc. Chap 9-11 How to Choose between Type I and Type II Errors Choice Depends on the Cost of the Errors Choose Smaller Type I Error when the Cost of Rejecting the Maintained Hypothesis is High A criminal trial: convicting an innocent person The Exxon Valdez: Causing an oil tanker to sink Choose Larger Type I Error when You Have an Interest in Changing the Status Quo A decision in a startup company about a new piece of software A decision about unequal pay for a covered group

© 2001 Prentice-Hall, Inc. Chap 9-12 Level of Significance, Defines Unlikely Values of Sample Statistic if Null Hypothesis is True Called rejection region of the sampling distribution Designated by, (level of significance) Typical values are.01,.05,.10 Selected by the Researcher at the Beginning Determine the Probability of Committing a Type I Error Provides the Critical Value(s) of the Test

© 2001 Prentice-Hall, Inc. Chap 9-13 Hypothesis Testing Process Identify the Population Assume the population mean age is 50. ( ) REJECT Take a Sample Null Hypothesis No, not likely!

© 2001 Prentice-Hall, Inc. Chap 9-14 It is unlikely that we would get a sample mean of this value if in fact this were the population mean.... Therefore, we reject the null hypothesis that = 50. Reason for Rejecting H 0 Sampling Distribution of 20 If H 0 is true

© 2001 Prentice-Hall, Inc. Chap 9-15 Level of Significance and the Rejection Region H 0 :   50 H 1 :  < H 0 :   50 H 1 :  > 50 H 0 :   50 H 1 :   50    /2 Critical Value(s) Rejection Regions

© 2001 Prentice-Hall, Inc. Chap 9-16 Factors Affecting Type II Error True Value of Population Parameter increases when the difference between hypothesized parameter and its true value decrease Significance Level increases when decreases Population Standard Deviation increases when increases Sample Size increases when n decreases n

© 2001 Prentice-Hall, Inc. Chap 9-17 Summary Addressed Hypothesis Testing Methodology