Course Detail (Course Description By Faculty)

Business Statistics (41000)

Data science. Machine learning. Statistics. Predictive Analytics. No matter what it’s called, modern business runs on data. This course is an introduction to the fundamentals of probability and statistics with an aim towards building foundational skills in modern data science. Topics to be covered include 1) Exploratory data analysis and descriptive statistics, 2) Basic probability, common pitfalls and fallacies, 3) Statistical modeling, inference, p-values, and A/B testing, and 4) Prediction, regression, and classification. Emphasis will be placed on ethics and privacy in data analysis as well as real-world applications and case studies.

  • No non-Booth Students
No pass/fail grades. No auditors.
  • No auditors
  • No pass/fail grades
Description and/or course criteria last updated: February 21 2024
SCHEDULE
  • Spring 2024
    Section: 41000-02
    MW 10:10 AM-11:30 AM
    Harper Center
    C05
    In-Person Only

Business Statistics (41000) - Deb, Nabarun>>

Data science. Machine learning. Statistics. Predictive Analytics. No matter what it’s called, modern business runs on data. This course is an introduction to the fundamentals of probability and statistics with an aim towards building foundational skills in modern data science. Topics to be covered include 1) Exploratory data analysis and descriptive statistics, 2) Basic probability, common pitfalls and fallacies, 3) Statistical modeling, inference, p-values, and A/B testing, and 4) Prediction, regression, and classification. Emphasis will be placed on ethics and privacy in data analysis as well as real-world applications and case studies.

  • No non-Booth Students
No pass/fail grades. No auditors.
  • No auditors
  • No pass/fail grades
Description and/or course criteria last updated: February 21 2024
SCHEDULE
  • Spring 2024
    Section: 41000-02
    MW 10:10 AM-11:30 AM
    Harper Center
    C05
    In-Person Only