This course provides a comprehensive introduction to the fundamental concepts and methods of probability and statistics. It is designed to equip students with the skills to collect, organize, analyze, and interpret data to make informed decisions.
The first part of the course focuses on probability theory, including an exploration of basic probability rules, conditional probability, random variables, and common discrete and continuous probability distributions (such as binomial, Poisson, and normal distributions).
The second part of the course delves into statistical inference. Key topics include descriptive statistics, sampling distributions, parameter estimation, hypothesis testing, confidence intervals, and an introduction to linear regression and correlation. The course emphasizes both the theoretical underpinnings and the practical application of statistical methods, often using statistical software to analyze real-world datasets.
Prerequisites: College Algebra [MAT117 or equivalent]
- Teacher: Geoffrey Thursten
- Teacher: Admin User