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Lecture Business statistics in practice (7/e): Chapter 11 - Bowerman, O'Connell, Murphree

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Chapter 11 - Statistical inferences for population variances. After mastering the material in this chapter, you will be able to: Explain the basic terminology and concepts of experimental design, compare several different population means by using a one-way analysis of variance, compare treatment effects and block effects by using a randomized block design,...

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  1. Chapter 11 Statistical Inferences for Population  Variances McGraw­Hill/Irwin Copyright © 2014 by The McGraw­Hill Companies, Inc. All rights reserved.
  2. Statistical Inferences for Population  Variances 11.1 The Chi­Square Distribution 11.2 Statistical Inference for a Population  Variance 11.3 The F Distribution 11.4 Comparing Two Population Variances  by Using Independent Samples 11­2
  3. LO11-1: Describe the properties of the chi- square distribution and 11.1 The Chi­Square Distribution use a chi-square table. Sometimes make inferences using the chi­ square distribution ◦Denoted  ² Skewed to the right Exact shape depends on the degrees of  freedom ◦Denoted df  A chi­square point  ²α is the point under a chi­ square distribution that gives right­hand tail area  11­3
  4. LO11-2: Use the chi- square distribution to make statistical inferences about population variances. 11.1 Statistical Inference for  Population Variance If s2 is the variance of a random sample of n  measurements from a normal population  with variance σ2 The sampling distribution of the statistic (n ­ 1) s2 / σ2 is a chi­square distribution with  (n – 1) degrees of freedom Can calculate confidence interval and  perform hypothesis testing 100(1­α)% confidence interval for σ2 11­4
  5. LO11-2 Formulas 2 A 100(1 ­ ) percent confidence interval for   is (n 1) s 2 (n 1) s 2 2 , 2 /2 1 /2 2 2 We can test H 0 : 0  at   using the test statistic 2 n 1 s2 2 0 11­5
  6. LO11-3: Describe the properties of the F distribution and use on 11.3 F Distribution F table. Figure 11.5 11­6
  7. LO11-3 F Distribution Tables The F point F  is the point on the horizontal  axis under the curve of the F distribution that  gives a right­hand tail area equal to  The value of F  depends on a (the size of the  right­hand tail area) and df1 and df2 Different F tables for different values of  ◦Tables A.6 for   = 0.10 ◦Tables A.7 for   = 0.05 ◦Tables A.8 for   = 0.025 ◦Tables A.9 for   = 0.01 11­7
  8. LO11-4: Compare two population variances when the samples are independent. 11.4 Comparing Two Population  Variances by Using Independent Samples  Population 1 has variance σ12 and population 2 has  variance σ22  The null hypothesis H0 is that the variances are the  same ◦ H0: σ12 = σ22  The alternative is that one is smaller than the other ◦ That population has less variable measurements ◦ Suppose σ12 > σ22 ◦ More usual to normalize  Test H0: σ12/σ22 = 1 vs. σ12/σ22 > 1 11­8
  9. LO11-4 Comparing Two Population Variances  Continued  Reject H0 in favor of Ha if s12/s22 is significantly  greater than 1  s12 is the variance of a random of size n1 from a  population with variance σ12   s22 is the variance of a random of size n2 from a  population with variance σ22  To decide how large s12/s22 must be to reject H0,  describe the sampling distribution of s12/s22  The sampling distribution of s12/s22 is the F  distribution 11­9
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