2020-2021 Undergraduate Academic Catalog 
    
    Sep 21, 2021  
2020-2021 Undergraduate Academic Catalog [ARCHIVED CATALOG]

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AC 2303 - AS Lab I: Applications of Probability

3 lecture hours 0 lab hours 3 credits
Course Description
This course covers the applications of the probability concepts and theory that students learned in MA 2630  and MA 2631 . The students will apply the tools they learned in these two probability courses to problems encountered in actuarial science for assessing risk.  (prereq: MA 2631 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Calculate probabilities of mutually exclusive events
  • Calculate probabilities using addition and multiplication rules
  • Calculate probabilities using combinations and permutations
  • Calculate conditional probabilities
  • Use Bayes theorem to calculate probabilities
  • Apply probability mass, probability density, and cumulative distribution functions
  • Calculate expected value, mode, median, variance, and standard deviation
  • Calculate probabilities using probability generating and moment generating functions
  • Perform calculations concerning joint probability and probability density functions, and cumulative distribution functions
  • Determine conditional and marginal probability and probability density functions, cumulative distribution functions
  • Calculate moments for joint, conditional and marginal random variables
  • Apply joint moment generating functions
  • Calculate variance and standard deviation for conditional and marginal probability distributions
  • Calculate joint moments, such as covariance and correlation coefficient

Prerequisites by Topic
  • Combinatorial probability
  • Probability rules 
  • Conditional probability
  • Total probability law and Bayes theorem
  • Discrete random variables
  • Binomial, Poisson, geometric, and other discrete distributions
  • Continuous random variables
  • Normal, chi-Square, t-distribution and other continuous distributions
  • Mixed random variables
  • Marginal distribution
  • Moment generating functions
  • Measures of central tendency and dispersion

Course Topics
  • Application of probabilities of mutually exclusive events
  • Applications of probabilities using addition and multiplication rules
  • Applications of probabilities using combinations and permutations
  • Applications of conditional probabilities
  • Applications of Bayes theorem to calculate probabilities
  • Probability mass, probability density, and cumulative distribution function applications
  • Applications of expected value, mode, median, variance and standard deviation
  • Calculate probabilities using probability generating and moment generating functions
  • Applications of joint probability and probability density functions and cumulative distribution functions
  • Applications of conditional and marginal probability and probability density functions, cumulative distribution functions
  • Applications of moments for joint, conditional, and marginal random variables
  • Applications of variance and standard deviation for conditional and marginal probability distributions
  • Applications of joint moments, such as covariance and correlation coefficient

Coordinator
Dr. Yvonne Yaz



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