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MATH 345 : Probability and Statistics I

Credits: 3

Course Description: This course presents the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal. Topics also include basic ideas and techniques of statistical analysis.

Pre-Requisites: MATH 141 or permission of instructor.

Sample Materials

  1. Sample spaces, events;
  2. Counting problems; permutations, combinations, binomial coefficients;
  3. Axioms of probability, combinatorial probability,
  4. Conditional probability, Bayes’ formula; independence;
  5. Random variables, types of random variables: discrete and continuous;
  6. Density and distribution functions;
  7. Joint distribution, marginals,
  8. Independence of random variables, conditional distribution;
  9. Expected value, variance, standard deviation;
  10. Moments, moment generating function;
  11. Covariance, correlation, conditional expectation;
  12. Special discrete random distributions: Bernoulli, binomial, Poisson;
  13. Special continuous random distributions: normal, exponential, gamma;
  14. Central Limit Theorem;
  15. Parameter estimation, hypothesis testing;
  16. t-test, chi-square test
Fall 2017 Schedule:

Section Meetings Instructor Comments
TuTh 04:00pm - 05:15pm
Noël, Alfred
MW 04:00pm - 05:15pm
Degras-Valabregue, David

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