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Bivariate Normal Distribution

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Continuous Bivariate Distributions

Abstract

In introductory statistics courses, one has to know why the (univariate) normal distribution is important—especially that the random variables that occur in many situations are approximately normally distributed and that it arises in theoretical work as an approximation to the distribution of many statistics, such as averages of independent random variables. More or less, the same reasons apply to the bivariate normal distribution. “But the prime stimulus has undoubtedly arisen from the strange tractability of the normal model: a facility of manipulation which is absent when we consider almost any other multivariate data-generating mechanism.”—Barnett (1979).

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  1. Department of Mathematics & Statistics, McMaster University, 1280 Main St. W., L8S 4K1, Hamilton, ON, Canada

    Prof. N. Balakrishna

  2. Institute of Sciences and Technology, Massey University, 11222 Private Bag, Palmerston North, New Zealand

    Chin Diew Lai

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Balakrishna, N., Lai, C.D. (2009). Bivariate Normal Distribution. In: Continuous Bivariate Distributions. Springer, New York, NY. https://doi.org/10.1007/b101765_12

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