MATH - 371. Probability for Statistics

3 credit(s)
The course introduces mathematical probability to understand variation and variability. Methods of enumeration, conditional probability, independent events, and Bayes’ Theorem are developed in a general environment. Among the continuous and discrete probability distributions derived and studied are the Bernoulli distribution and distributions based on it, the uniform, exponential, normal, Gamma and Chi Square distributions. The Central Limit Theorem leads to approximations for discrete distributions. Chebyshev’s Inequality prepares the students for Inferential Statistics. Offered Spring semester.

Prerequisite(s): MATH 210 (may be taken concurrently).
Attribute: ARTS, DASC, MHUL