The Normality Assumption

  • Ashish Sen
  • Muni Srivastava
Part of the Springer Texts in Statistics book series (STS)


In much of the work presented in the last four chapters we have assumed that the Gauss-Markov conditions were true, We have also sometimes made the additional assumption that the errors and, therefore, the dependent variables were normally distributed. In practice, these assumptions do not always hold; in fact, quite often, at least one of them will be violated. In this and the next four chapters we shall examine how to check whether each of the assumptions actually holds and what, if anything, we can do if it does not. This chapter is devoted to the normality assumption.


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Copyright information

© Springer-Verlag New York Inc. 1990

Authors and Affiliations

  • Ashish Sen
    • 1
  • Muni Srivastava
    • 2
  1. 1.College of Architecture, Art, and Urban Planning School of Urban Planning and PolicyThe University of IllinoisChicagoUSA
  2. 2.Department of StatisticsUniversity of TorontoTorontoCanada

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