STATISTICS FOR COMPUTING AND DATA SCIENCE

Credit Hours: 3 · Graduate

Probability and statistics are essential tools in computer science and data science. They are at the heart of areas such as efficiency analysis of algorithms and randomized algorithms and central to fields like bioinformatics, social informatics, and, of course, machine learning. Furthermore, probability and statistics are essential for data science, as they are the foundation for quantifying uncertainty and assessing support for hypotheses and derived models. This course covers topics in probability and statistics, including probability and random variables, basic stochastic processes, basic descriptive statistics, and various methods for statistical inference and measuring support. In order to enroll in an online section of this course, you are expected to have a working camera and microphone. During class sessions, you must be able to participate using your microphone and you are expected to have your camera on for the duration of the class so that you are visible to the instructor and other students in the class, just as you would be in an in-person class.