# Introduction Hypothesis Testing

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01-Nov-2014Category

## Education

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### Transcript of Introduction Hypothesis Testing

- 1. Chapter 8 HandoutIntroduction to Hypothesis Testing: One Population Value
- 2. Chapter 8 SummaryHypothesis Testing for One Population Value:1. Population Mean () . (population standard deviation) is given (known): Use z/standard normal/bell shaped distribution . (pop std dev) is not given but s (sample std dev) is given Use students t distribution2. Population proportion () Use z/standard normal/bell shaped distribution3. Population variance (2) Use 2 (Chi-Square) distribution PS: population standard deviation =
- 3. What is a Hypothesis?A hypothesis is an I assume the mean GPAassumption about the of this class is 3.5!population parameter. A parameter is a Population mean or proportion The parameter must be identified before analysis. 1984-1994 T/Maker Co.
- 4. The Null Hypothesis, H0 States the Assumption (numerical) to be tested e.g. The average # TV sets in US homes is at least 3 (H0: 3) Begin with the assumption that the null hypothesis is TRUE. (Similar to the notion of innocent until proven guilty) Refers to the Status Quo Always contains the = signThe Null Hypothesis may or may not berejected.
- 5. The Alternative Hypothesis, H1or HA Is the opposite of the null hypothesis e.g. The average # TV sets in US homes is less than 3 (H1: < 3) Challenges the Status Quo Never contains the = sign The Alternative Hypothesis may or may not be accepted
- 6. Identify the ProblemSteps: State the Null Hypothesis (H : 3) 0 State its opposite, the Alternative Hypothesis (H1: < 3) Hypotheses are mutually exclusive & exhaustive Sometimes it is easier to form the alternative hypothesis first.
- 7. Hypothesis Testing Process Assume the population mean age is 50. (Null Hypothesis) Population The SampleIs X = 20 = 50? Mean Is 20 No, not likely! REJECT Null Hypothesis Sample
- 8. Reason for Rejecting H0Sampling Distribution It is unlikely that we would ... Therefore, we get a sample reject the null mean of this hypothesis that value ... = 50. ... if in fact this were the population mean. 20 = 50 Sample Mean H0
- 9. Level of Significance, Defines Unlikely Values of Sample Statistic if Null Hypothesis Is True Called Rejection Region of Sampling Distribution Designated (alpha) Typical values are 0.01, 0.05, 0.10 Selected by the Researcher at the Start Provides the Critical Value(s) of the Test
- 10. Level of Significance, and the Rejection Region H0: 3 CriticalH1: < 3 Value(s) Rejection 0 Regions H0: 3H1: > 3 0 /2H0: = 3H1: 3 0
- 11. Errors in Making Decisions Type I Error Reject True Null Hypothesis Has Serious Consequences Probability of Type I Error Is Called Level of Significance Type II Error Do Not Reject False Null Hypothesis Probability of Type II Error Is (Beta)
- 12. Result Possibilities H0: Innocent Jury Trial Hypothesis Test Actual Situation Actual SituationVerdict Innocent Guilty Decision H0 True H0 False Do Not Type IIInnocent Correct Error Reject 1- Error ( ) H0 Type I PowerGuilty Error Correct Reject Error H0 (1 - ) ( )
- 13. & Have an Inverse Relationship Reduce probability of one error and the other one goes up.
- 14. Factors Affecting Type II Error, True Value of Population Parameter Increases When Difference Between Hypothesized Parameter & True Value Decreases Significance Level Increases When Decreases Population Standard Deviation Increases When Increases Sample Size n Increases When n Decreases n
- 15. 3 Methods for Hypotheses TestsRefer to Figure 8-6 (page 299) for a hypothesis test for means () with (pop. std. dev.) is given:Method 1: Comparing X (X critical) with XMethod 2: Z test, i.e., comparing Z ( critical) with Z (or Z statistics or Z calculated)Method 3: Comparing (significance level) with p-valueYou can modify those three methods for other cases. For example, if is unknown, you must use students t distribution. If you would like to use Method 2, please compare t (t critical) with t (or t statistics or t calculated). Refer to Figure 8-8 (page 303).
- 16. You always get: Z ( critical) from Z distribution t (t critical) from students t distribution .2 (2critical) from 2distributionYou always get: Z or Z calculated or Z statistics from sample (page 299 and Figure 8-6) t or t calculated or t statistics from sample (Figure 8-8, page 299) .2 or 2 calculated or 2 statistics from sample (Figure 8-19, page 322)
- 17. Z-Test Statistics ( Known) Convert Sample Statistic (e.g., X ) to Standardized Z Variable X X X Z= = Test Statistic X n Compare to Critical Z Value(s) If Z test Statistic falls in Critical Region, Reject H0; Otherwise Do Not Reject H0
- 18. p Value Test Probability of Obtaining a Test Statistic More Extreme ( or ) than Actual Sample Value Given H0 Is True Called Observed Level of Significance Smallest Value of a H0 Can Be Rejected Used to Make Rejection Decision If p value , Do Not Reject H0 If p value < , Reject H0
- 19. Hypothesis Testing: StepsTest the Assumption that the true mean # of TV sets in US homes is at least 3.1. State H0 H0 : 32. State H1 H1 : < 33. Choose = .054. Choose n n = 1005. Choose Method: Z Test (Method 2)
- 20. Hypothesis Testing: Steps (continued) Test the Assumption that the average # of TV sets in US homes is at least 3. 6. Set Up Critical Value(s) Z = -1.645 7. Collect Data 100 households surveyed 8. Compute Test Statistic Computed Test Stat.= -2 9. Make Statistical Decision Reject Null Hypothesis10. Express Decision The true mean # of TV set is less than 3 in the US households.
- 21. One-Tail Z Test for Mean ( Known) Assumptions Population Is Normally Distributed If Not Normal, use large samples Null Hypothesis Has =, , or Sign Only Z Test Statistic: x x x z= = x n
- 22. Rejection Region H0: 0 H0: 0 H1: < 0 H1: > 0Reject H0 Reject H 0 0 Z 0 Z Must Be Significantly Small values dont contradict H0 Below = 0 Dont Reject H0!