MA 385, Introduction to Probability
Course Description and Goals
This course is a calculus-based introduction to probability with special emphasis on the interplay between probability and statistics. Topics include
- descriptive statistics
- probability spaces
- discrete distributions (including the binomial, geometric, hypergeometric, and Poisson)
- continuous distributions (including the uniform, exponential, and normal)
- joint distributions
- mean, variance, and general expected value
- independence and correlation
- the law of large numbers
- the central limit theorem.
Goals of the course include
- A basic understanding of the special language, notation, and point of view of probability.
- A basic understanding of the interplay between probability and inferential statistics.
- The ability to solve standard computational problems in probability.
- The ability to recognize special models, including Bernoulli trials, finite sampling models, and the Poisson model
- An intuitive understanding the two fundamental theorems of probability: he law of large numbers and the central limit theorem
- An improve ability to read, write, speak, and think in mathematical terms.
This course also prepares students for further study, including MA 487, Introduction to Mathematical Statistics and MA 585, Probability.
Prerequisites and Restrictions
MA 120, Calculus with Applications or MA 172, Calculus B, and one MA course at the 200-level or above. No credit given to students who have successfully completed MA 585, Probability.
3 Semester Hours
This course is graded A, B, C, D, F. The grade typically depends on a combination of class tests, homework or quizzes, and a comprehensive final exam.