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, 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.