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.
Prerequisites and Restrictions
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.
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