Basic Testing for Categorical Data

  • Tamás Rudas
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

This chapter first discusses tests of hypotheses pertaining to the probability of a binomial distribution and gives a brief review of the fundamental concepts of tests of hypotheses. Exact, randomized, and asymptotic tests are considered. The Pearson chi-squared and likelihood ratio statistics are introduced for tests of fit. The concept of independence, which will play a central role in later chapters of the book, is also introduced for the simple case of two-way tables and tests of independence are discussed.

References

  1. 1.
    Agresti, A.: Categorical Data Analysis, 2nd ed. Wiley, New York (2002)CrossRefMATHGoogle Scholar
  2. 13.
    Bishop, Y.M.M., Fienberg, S.E.,Holland, P.W.: Discrete Multivariate Analysis: Theory and Practice. MIT Press, Boston (1975)MATHGoogle Scholar
  3. 70.
    Rudas, T.: A Monte Carlo comparison of the small sample behaviour of the Pearson, the likelihood ratio and the Cressie-Read statistics. Journal of Statistical Computation and Simulation, 24, 107–120 (1986)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Tamás Rudas
    • 1
    • 2
  1. 1.Center for Social SciencesHungarian Academy of SciencesBudapestHungary
  2. 2.Eötvös Loránd UniversityBudapestHungary

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