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MTH418 Statistical Analysis

Lead Faculty: Dr Igor Ya Subbotin

Course Description

An examination of statistical applications to business, computer science, psychology, education, social sciences, and mathematics with fundamental concepts of probability distribution, mathematical models relating independent and dependent random variables, hypothesis testing and experimental design. Includes fundamental analysis of variance, various distributions and methods of regression, analysis and scaling.

Learning Outcomes

  • Analyze the characteristics of distributions including central tendency and dispersion.
  • Define probability, probability distributions, random variables, and expectation of events.
  • Choose between and use binomial distribution, Poisson processes, normal distribution.
  • Compute and utilize probability densities, the gamma distribution, the beta distribution, the Weibull distribution.
  • Recognize sampling distribution and statistical inference.
  • Determine rejection of outliers, distribution of extremes.
  • Apply the method of least squares to linear regression.
  • Demonstrate knowledge of P-values and hypothesis test.