Roberto Bertolusso

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.

This course provides a computational bridge for students who have completed STAT 310 to fulfill the requirements of the AI major. Students will implement statistical methodology using modern computational languages (such as Python), focusing on data structures, visualization, and simulation techniques essential for modern data science.

This course introduces students to the statistical programming language, R, and how to use it in statistical and data science problems. The course traces the data science pipeline from importing data into R, exploring and visualizing data, applying a variety of statistical methods, and communicating results. Important computational tools for data science (e.g. databases, web scraping, and big data) and good programming practice are integrated throughout the course. No programming experience is required. Cross-list: STAT 605. Mutually Exclusive: Cannot register for STAT 405 if student has credit for STAT 605.

This course introduces students to the statistical programming language, R, and how to use it in statistical and data science problems. The course traces the data science pipeline from importing data into R, exploring and visualizing data, applying a variety of statistical methods, and communicating results. Important computational tools for data science (e.g. databases, web scraping, and big data) and good programming practice are integrated throughout the course. No programming experience is required. STAT 605 includes more advanced assignments and/or examinations than STAT 405. Cross-list: STAT 405. Mutually Exclusive: Cannot register for STAT 605 if student has credit for STAT 405.