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IE1XX : Probability and Statistics

Prerequisites: None

Contents:

The course covers the basics on probability and statistics. Topics include:

  • Descriptive Statistics & Data Handling, 
  • Probability: Sample spaces & events, conditional probability, Notions of independent events, Bayes Theorem, Discrete and Continuous random variables; probability mass functions, density functions, distributions, Expectations & Variance & their properties, covariance, correlation
  • Conditional random variables, conditional expectations, joint and marginal distributions, laws of large numbers, Central Limit Theorem
  • Some of the useful & common Distributions such as Bernoulli, Binomial, Poisson, Exponential, Uniform, Normal
  • Statistical inference basics, including parameter estimation, hypothesis testing (t-test, chi-square tests)
  • Introduction to time series data
  • Examples and use of spreadsheets / software for computations
  • Applications to business decisions

References

  • Sheldon Ross, Introduction to Probability and Statistics for Engineers and Scientists, 5th Edition, Academic Press, 2014.
  • Maurice DeGroot and Mark Schiverser, Probability and Statistics, 4th edition, Pearson, 2011
  • Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer (2007) Mathematical Statistics with Applications, 7th edition, Duxbury Resource Center.