(BQ) Part 2 book "Statistics for economics, accounting and business studies" has contents: The χ2 and F distributions, correlation and regression, multiple regression, data collection and sampling methods, index numbers, seasonal adjustment of time-series data. | 26/02/2009 6 09:11 Page 204 The χ2 and F distributions Contents Learning outcomes Introduction The χ 2 distribution Estimating a variance Comparing actual and expected values of a variable Contingency tables Constructing the expected values Calculation of the test statistic The F distribution Testing the equality of two variances Analysis of variance The result of the hypothesis test The analysis of variance table Summary Key terms and concepts Problems Answers to exercises Appendix: Use of χ 2 and F distribution tables Learning outcomes By the end of this chapter you should be able to: ● understand the uses of two new probability distributions: χ2 and F; ● construct confidence interval estimates for a variance; ● perform hypothesis tests concerning variances; ● analyse and draw inferences from data contained in contingency tables; ● construct a simple analysis of variance table and interpret the results. Complete your diagnostic test for Chapter 6 now to create your personal study plan. Exercises with an icon ? are also available for practice in MathXL with additional supporting resources. 204 204 205 205 206 208 215 216 218 220 220 222 226 227 229 230 231 234 236 26/02/2009 09:11 Page 205 The χ2 distribution Introduction The final two distributions to be studied are the χ2 (pronounced ‘kye-squared’) and F distributions. Both of these distributions have a variety of uses, the most common of which are illustrated in this chapter. These distributions allow us to extend some of the estimation and testing procedures covered in Chapters 4 and 5. The χ2 distribution allows us to establish confidence interval estimates for a variance, just as the Normal and t distributions were used in the case of a mean. Further, just as the Binomial distribution was used to examine situations where the result of an experiment could be either ‘success’ or ‘failure’, the χ2 distribution allows us to analyse situations where there are .
