IPAC 4130 - Data Analytics and Computational Statistics 1

3 hours

Provides an overview of quantitative methods essential for analyzing data, with an emphasis on science and industry applications. Topics include identification of appropriate metrics and measurement methods, descriptive and inferential statistics, experimental design, parametric and non-parametric tests, simulation, and linear and logistic regression, categorical data analysis, and select unsupervised learning techniques. Standard and open source statistical packages are used to apply techniques to real-world problems.

Prerequisite(s): MATH 1100 or MATH 1680 or equivalent, or consent of instructor.

Course specific fees (in addition to tuition and mandatory):
Academic (AF) per hour: $33.10