ENGR 241 Probability and Statistics with Data Science Applications
The course introduces probability and statistics concepts as needed for engineering students. The emphasis will be on applications of these formulas to solve problems. Concepts covered will include descriptive statistics, measures of location and of variability, data visualization, sample space and events, probability and independence, Bayes’ rule, random variables, densities and moments, normal distribution, the central limit theorem, confidence intervals, hypothesis testing and p-values, and applications for prediction in a least squares linear regression model. The class will use a state-of-the-art data science programming language to complete the coursework.
Distribution
School of Engineering and Science