AP Statistics. Chap 13-1 Chapter 13 Estimation and Hypothesis Testing for Two Population Parameters

AP Statistics Chap 13-2 Chapter Goals After completing this chapter, you should be able to: Test hypotheses or form interval estimates for two independent population means Standard deviations known Standard deviations unknown two means from paired samples the difference between two population proportions

AP Statistics Chap 13-3 Estimation for Two Populations Estimating two population values Population means, independent samples Paired samples Population proportions Group 1 vs. independent Group 2 Same group before vs. after treatment Proportion 1 vs. Proportion 2 Examples:

AP Statistics Chap 13-4 Difference Between Two Means Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 Goal: Form a confidence interval for the difference between two population means, μ 1 – μ 2 The point estimate for the difference is x 1 – x 2 *

AP Statistics Chap 13-5 Independent Samples Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 Different data sources Unrelated Independent Sample selected from one population has no effect on the sample selected from the other population Use the difference between 2 sample means Use z test or pooled variance t test *

AP Statistics Chap 13-6 Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 known Assumptions:  Samples are randomly and independently drawn  population distributions are normal or both sample sizes are  30  Population standard deviations are known *

AP Statistics Chap 13-7 Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 …and the standard error of x 1 – x 2 is When σ 1 and σ 2 are known and both populations are normal or both sample sizes are at least 30, the test statistic is a z-value… (continued) σ 1 and σ 2 known *

AP Statistics Chap 13-8 Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 The confidence interval for μ 1 – μ 2 is: σ 1 and σ 2 known (continued) *

AP Statistics Chap 13-9 Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, large samples Assumptions:  Samples are randomly and independently drawn  both sample sizes are  30  Population standard deviations are unknown *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, large samples Forming interval estimates:  use sample standard deviation s to estimate σ  the test statistic is a z value (continued) *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 The confidence interval for μ 1 – μ 2 is: σ 1 and σ 2 unknown, large samples (continued) *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, small samples Assumptions:  populations are normally distributed  the populations have equal variances  samples are independent *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, small samples Forming interval estimates:  The population variances are assumed equal, so use the two sample standard deviations and pool them to estimate σ  the test statistic is a t value with (n 1 + n 2 – 2) degrees of freedom (continued) *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, small samples The pooled standard deviation is (continued) *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 The confidence interval for μ 1 – μ 2 is: σ 1 and σ 2 unknown, small samples (continued) Where t  /2 has (n 1 + n 2 – 2) d.f., and *

AP Statistics Chap Paired Samples Tests Means of 2 Related Populations Paired or matched samples Repeated measures (before/after) Use difference between paired values: Eliminates Variation Among Subjects Assumptions: Both Populations Are Normally Distributed Or, if Not Normal, use large samples Paired samples d = x 1 - x 2

AP Statistics Chap Paired Differences The i th paired difference is d i, where Paired samples d i = x 1i - x 2i The point estimate for the population mean paired difference is d : The sample standard deviation is n is the number of pairs in the paired sample

AP Statistics Chap Paired Differences The confidence interval for d is Paired samples Where t  /2 has n - 1 d.f. and s d is: (continued) n is the number of pairs in the paired sample

AP Statistics Chap Hypothesis Tests for the Difference Between Two Means Testing Hypotheses about μ 1 – μ 2 Use the same situations discussed already: Standard deviations known or unknown Sample sizes  30 or not  30

AP Statistics Chap Hypothesis Tests for Two Population Proportions Lower tail test: H 0 : μ 1  μ 2 H A : μ 1 < μ 2 i.e., H 0 : μ 1 – μ 2  0 H A : μ 1 – μ 2 < 0 Upper tail test: H 0 : μ 1 ≤ μ 2 H A : μ 1 > μ 2 i.e., H 0 : μ 1 – μ 2 ≤ 0 H A : μ 1 – μ 2 > 0 Two-tailed test: H 0 : μ 1 = μ 2 H A : μ 1 ≠ μ 2 i.e., H 0 : μ 1 – μ 2 = 0 H A : μ 1 – μ 2 ≠ 0 Two Population Means, Independent Samples

AP Statistics Chap Hypothesis tests for μ 1 – μ 2 Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 Use a z test statistic Use s to estimate unknown σ, approximate with a z test statistic Use s to estimate unknown σ, use a t test statistic

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 The test statistic for μ 1 – μ 2 is: σ 1 and σ 2 known *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, large samples The test statistic for μ 1 – μ 2 is: *

AP Statistics Chap Population means, independent samples σ 1 and σ 2 known σ 1 and σ 2 unknown, n 1 and n 2  30 σ 1 and σ 2 unknown, n 1 or n 2 < 30 σ 1 and σ 2 unknown, small samples The test statistic for μ 1 – μ 2 is: *

AP Statistics Chap Two Population Means, Independent Samples Lower tail test: H 0 : μ 1 – μ 2  0 H A : μ 1 – μ 2 < 0 Upper tail test: H 0 : μ 1 – μ 2 ≤ 0 H A : μ 1 – μ 2 > 0 Two-tailed test: H 0 : μ 1 – μ 2 = 0 H A : μ 1 – μ 2 ≠ 0  /2  -z  -z  /2 zz z  /2 Reject H 0 if z < -z  Reject H 0 if z > z  Reject H 0 if z < -z  /2  or z > z  /2 Hypothesis tests for μ 1 – μ 2

AP Statistics Chap Pooled s p t Test: Example You’re a financial analyst for a brokerage firm. Is there a difference in dividend yield between stocks listed on the NYSE & NASDAQ? You collect the following data: NYSE NASDAQ Number Sample mean Sample std dev Assuming equal variances, is there a difference in average yield (  = 0.05)?

AP Statistics Chap Calculating the Test Statistic The test statistic is:

AP Statistics Chap Solution H 0 : μ 1 - μ 2 = 0 i.e. (μ 1 = μ 2 ) H A : μ 1 - μ 2 ≠ 0 i.e. (μ 1 ≠ μ 2 )  = 0.05 df = = 44 Critical Values: t = ± Test Statistic: Decision: Conclusion: Reject H 0 at  = 0.05 There is evidence of a difference in means. t Reject H

AP Statistics Chap The test statistic for d is Paired samples Where t  /2 has n - 1 d.f. and s d is: n is the number of pairs in the paired sample Hypothesis Testing for Paired Samples

AP Statistics Chap Lower tail test: H 0 : μ d  0 H A : μ d < 0 Upper tail test: H 0 : μ d ≤ 0 H A : μ d > 0 Two-tailed test: H 0 : μ d = 0 H A : μ d ≠ 0 Paired Samples Hypothesis Testing for Paired Samples  /2  -t  -t  /2 tt t  /2 Reject H 0 if t < -t  Reject H 0 if t > t  Reject H 0 if t < -t   or t > t  Where t has n - 1 d.f. (continued)

AP Statistics Chap Assume you send your salespeople to a “customer service” training workshop. Is the training effective? You collect the following data: Paired Samples Example Number of Complaints: (2) - (1) Salesperson Before (1) After (2) Difference, d i C.B T.F M.H R.K M.O d =  didi n = -4.2

AP Statistics Chap  Has the training made a difference in the number of complaints (at the 0.01 level)? - 4.2d = H 0 : μ d = 0 H A :  μ d  0 Test Statistic: Critical Value = ± d.f. = n - 1 = 4 Reject  / Decision: Do not reject H 0 (t stat is not in the reject region) Conclusion: There is not a significant change in the number of complaints. Paired Samples: Solution Reject  /  =.01

Technology Toolbox AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con’t AP Statistics Chap TI-83/84 TI-89

AP Statistics Chap Two Population Proportions Goal: Form a confidence interval for or test a hypothesis about the difference between two population proportions, p 1 – p 2 The point estimate for the difference is p 1 – p 2 Population proportions Assumptions: n 1 p 1  10, n 1 (1-p 1 )  10 n 2 p 2  10, n 2 (1-p 2 )  10

AP Statistics Chap Confidence Interval for Two Population Proportions Population proportions The confidence interval for p 1 – p 2 is:

AP Statistics Chap Hypothesis Tests for Two Population Proportions Population proportions Lower tail test: H 0 : p 1  p 2 H A : p 1 < p 2 i.e., H 0 : p 1 – p 2  0 H A : p 1 – p 2 < 0 Upper tail test: H 0 : p 1 ≤ p 2 H A : p 1 > p 2 i.e., H 0 : p 1 – p 2 ≤ 0 H A : p 1 – p 2 > 0 Two-tailed test: H 0 : p 1 = p 2 H A : p 1 ≠ p 2 i.e., H 0 : p 1 – p 2 = 0 H A : p 1 – p 2 ≠ 0

AP Statistics Chap Two Population Proportions Population proportions The pooled estimate for the overall proportion is: where x 1 and x 2 are the numbers from samples 1 and 2 with the characteristic of interest Since we begin by assuming the null hypothesis is true, we assume p 1 = p 2 and pool the two p estimates

AP Statistics Chap Two Population Proportions Population proportions The test statistic for p 1 – p 2 is: (continued)

AP Statistics Chap Hypothesis Tests for Two Population Proportions Population proportions Lower tail test: H 0 : p 1 – p 2  0 H A : p 1 – p 2 < 0 Upper tail test: H 0 : p 1 – p 2 ≤ 0 H A : p 1 – p 2 > 0 Two-tailed test: H 0 : p 1 – p 2 = 0 H A : p 1 – p 2 ≠ 0  /2  -z  -z  /2 zz z  /2 Reject H 0 if z < -z  Reject H 0 if z > z  Reject H 0 if z < -z   or z > z 

AP Statistics Chap Example: Two population Proportions Is there a significant difference between the proportion of men and the proportion of women who will vote Yes on Proposition A? In a random sample, 36 of 72 men and 31 of 50 women indicated they would vote Yes Test at the.05 level of significance

AP Statistics Chap The hypothesis test is: H 0 : p 1 – p 2 = 0 (the two proportions are equal) H A : p 1 – p 2 ≠ 0 (there is a significant difference between proportions) The sample proportions are: Men: p 1 = 36/72 =.50 Women: p 2 = 31/50 =.62  The pooled estimate for the overall proportion is: Example: Two population Proportions (continued)

Technology Toolbox AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con AP Statistics Chap TI-83/84 TI-89

Technology Toolbox con AP Statistics Chap TI-83/84 TI-89

AP Statistics Chap TI-83/84 TI-89

AP Statistics Chap Chapter Summary Compared two independent samples Formed confidence intervals for the differences between two means Performed Z test for the differences in two means Performed t test for the differences in two means Compared two related samples (paired samples) Formed confidence intervals for the paired difference Performed paired sample t tests for the mean difference Compared two population proportions Formed confidence intervals for the difference between two population proportions Performed Z-test for two population proportions