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Analysis of Variance and Chi-Square Tests

In: Statistics for Business and Financial Economics

Author

Listed:
  • Cheng-Few Lee

    (Rutgers University Business School, Department of Finance and Economics)

  • John C. Lee

    (Center for PBBEF Research)

  • Alice C. Lee

Abstract

Both χ 2 and F distributions and their related testing statistics have been discussed in detail in the last three chapters. In this chapter, we will talk about how these two distributions can be used to do data analysis involving the means or the proportions of more than two populations. In other words, we will develop an understanding of (1) a technique known as analysis of variance (ANOVA), which enables us to test the significance of the differences among sample means in terms of an F distribution and (2) tests of goodness of fit and independence in an x 2 distribution. The ANOVA is used to test the equality of more than two population means. The goodness-of-fit test is used to test the equality of more than two population proportions or to assess the appropriateness of a distribution. The test of independence determines whether the differences among several sample proportions are significant or are instead likely to be due to chance alone.

Suggested Citation

  • Cheng-Few Lee & John C. Lee & Alice C. Lee, 2013. "Analysis of Variance and Chi-Square Tests," Springer Books, in: Statistics for Business and Financial Economics, edition 3, chapter 0, pages 543-612, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-5897-5_12
    DOI: 10.1007/978-1-4614-5897-5_12
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