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Non-Parametric Statistics: Course Outline

Non-parametric methods are used to make inferences about infinite dimensional parameters in statistical models.

Course Outline

  • Scales of measurements.
  • Non-Parametric  problems.
  • When to use non-parametric procedures.
  • Parametric versus nonparametric tests.
  • Trimmed and Winsorized means.
  • One sample tests: Binomial test, Sign test.
  • Wilcoxan signed ranks test.
  • Rank Sum Test.
  • Kolmogrov-Smirnov test.
  • Run test.
  • Tests for two related samples: sign test, run test.      
  • Chi-square test.
  • Test for two independent samples: Mann-Whitney test.
  • Median test.        
  • Chi-square test.
  • Wald-wolfwitz test,
  • Kolmogrov-Smirnov test.
  • Categorical data.
  • Association in r.
  • C contingency tables.
  • Partition of c2.
  • Binomial and Poisson.
  • Homogeneity tests.
  • Log-Linear models.

E-Books (Full Text)

E-Books (Full Text)