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Continuous Variates

  • J. G. Kalbfleisch
Part of the Springer Texts in Statistics book series (STS)

Abstract

There are many quantities such as time, weight, length, temperature, etc., which we naturally think of as continuous variables; that is, as variables capable of taking any real value in some range. These are represented in probability theory by continuous variates, which we define in Section 1 below. Generally speaking, continuous variates are handled mathematically in much the same way as discrete variates, with sums in the discrete case being replaced by integrals in the continuous case. However, there is a difference in change of variables problems, since the Jacobian of the transformation plays a role in the continuous case but not in the discrete case.

Keywords

Probability Density Function Cumulative Distribution Function Exponential Distribution Central Limit Theorem Hazard Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1985

Authors and Affiliations

  • J. G. Kalbfleisch
    • 1
  1. 1.Department of Statistics and Actuarial ScienceUniversity of WaterlooWaterlooCanada

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