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Basic Statistical Concepts

  • Badi H. Baltagi

Abstract

One chapter cannot possibly review what one learned in one or two pre-requisite courses in statistics. This is an econometrics book, and it is imperative that the student have taken at least one solid course in statistics. The concepts of a random variable, whether discrete or continuous, and the associated probability function or probability density function (p.d.f.) are assumed known. Similarly, the reader should know the following statistical terms: Cumulative distribution function, marginal, conditional and joint p.d.f.’s. The reader should be comfortable with computing mathematical expectations, and familiar with the concepts of independence, Bayes Theorem and several continuous and discrete probability distributions. These distributions include: the Bernoulli, Binomial, Poisson, Geometric, Uniform, Normal, Gamma, Chi-squared (χ2), Exponential, Beta, t and F distributions.

Keywords

Maximum Likelihood Estimation Central Limit Theorem Critical Region Unbiased Estimator Moment Generate 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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Badi H. Baltagi
    • 1
  1. 1.Department of EconomicsTexas A&M UniversityCollege StationUSA

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