Susanna Lange

Susanna Lange
  • Lecturer in Statistics and Data Science

Contact Information

Teaching

Current Courses (Summer 2026)

  • STAT0001 - Intro To Stat & Data Sci

    In this course, we will learn introductory statistics using R with a focus on the application of statistical thinking to business problems. We will learn basic statistical concepts such as mean, variance, quantiles and hypothesis testing, and basic R programming for data management and analysis. We will work with traditional R's data, frame structure as well as the modern tibbles structure. Prerequisite: Percentages, average, powers, exponential, linear equation of a line, polynomials.

    STAT0001920 ( Syllabus )

All Courses

  • STAT0001 - Intro To Stat & Data Sci

    In this course, we will learn introductory statistics using R with a focus on the application of statistical thinking to business problems. We will learn basic statistical concepts such as mean, variance, quantiles and hypothesis testing, and basic R programming for data management and analysis. We will work with traditional R's data, frame structure as well as the modern tibbles structure. Prerequisite: Percentages, average, powers, exponential, linear equation of a line, polynomials.

  • STAT1010 - Intro Business Stat

    Data summaries and descriptive statistics; introduction to a statistical computer package; Probability: distributions, expectation, variance, covariance, portfolios, central limit theorem; statistical inference of univariate data; Statistical inference for bivariate data: inference for intrinsically linear simple regression models.

Knowledge at Wharton

Career Growth, Job Mobility, and the Modern Workforce

Wharton professor of management discusses how graduates should approach first jobs, career mobility, and long-term professional growth in today’s evolving economy.Read More

Knowledge @ Wharton - 5/13/2026
How Advanced Analytics Are Changing Professional Hockey

Leading hockey analytics expert discusses NHL playoff trends, player evaluation, tracking data, and how teams are using advanced models to gain a competitive edge.Read More

Knowledge @ Wharton - 5/13/2026
AI’s Supply Chain Problem

The scarcest resource in AI isn’t chips or talent — it’s grid capacity, writes Wharton’s Santiago Gallino.Read More

Knowledge @ Wharton - 5/12/2026