Course Detail

Business Statistics (41000)

Course Description by Faculty

  • Polson, Nicholas
  • Content
    For autumn quarter, this class will be offered in dual mode but it is possible that the faculty member will not be in the classroom.

    Bus41000 is a course on Data Analytics. Students will learn how to visualize and analyze data together with learning model building skills for analysis and prediction.

    This course provides an introduction to key concepts and data analytic tools that are applicable in business environments. Both basic underlying concepts and practical computational skills are covered.

    The techniques covered include (i) graphical data visualization; (ii) Bayes Probability; (iii) Statistical Modeling and Inference; (iv) A/B testing; (v) linear, logistic and multiple regression.

    This class uses R which is widely used in data science. Students are encouraged to familiarize themselves with the links and code available on the course website.
    Format
    • Lectures

    • Discussion

  • Prerequisites
    None.
  • Materials
    There are no required texts. Detailed lecture notes are available on the Course Website.
  • Grades
    Based on a midterm and a final project.
    Assessment & Testing
    • Midterm

    • Final exam (take home)

  • Syllabus
  • Autumn 2022Section: 41000-03W 8:30AM-11:30AMHarper CenterC01In-Person Only
  • Autumn 2022Section: 41000-85S 9:00AM-12:00PMGleacher Center204In-Person Only
Description and/or course criteria last updated: June 8 2022