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Statistics

The practice of advanced statistics normally requires the use of sophisticated software, not due to theoretical complexity but instead to sheer volume and repetition of required calculations. Without computers, advanced statistical number crunching would be too time consuming, especially with large data sets.

A course in advanced statistics will most likely follow the experience and particular interests of the professor in charge of the class. However, it is safe to say that whatever material is covered will most likely involve a sophisticated treatment of many of the following topics:

  • Descriptive statistical techniques
  • Probability theory
  • Random variables and probability distributions
  • Bivariate probability distributions
  • Discrete parametric probability distributions
  • Continuous parametric probability distributions
  • Sampling and the sampling distribution of a statistic
  • The chi-square, student's t, and Snedecor's F distributions
  • Point estimation and properties of point estimators
  • Interval estimation and confidence interval estimates
  • Tests of parametric statistical hypotheses
  • Nonparametric statistical techniques
  • Testing goodness of fit
  • Testing goodness of fit : contingency tables
  • Bivariate linear regression and correlation

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