HCM Introduction to Statistics

In this course, students will gain a foundation in what is called “model thinking” (i.e., the art of exploring the statistical properties of a dataset so as to choose the most appropriate statistical model). The course will start with statistical first moments—means, medians, and distributions—so that the students all have a strong foundation in the basics. Then, it will gradually move up to statistical inference—which is about deriving modeled estimates and testing the soundness of one statistic versus another. In an effort to make the material more engaging and real-world applicable, the course will be taught, primarily, through R programming (a free, open-source programming language, most famously used for statistical analysis.

More details

You'll Walk Away with

  • The ability to understand datasets using statistical best practices.
  • The ability to perform key statistical concepts like descriptive stats (means, medians, etc.), skew/kurtosis, correlation/covariance, regression, and categorical analysis.
  • The ability to export statistical results to CSV or MS Excel files and write a statistical analysis.

1 section

  • Spring 2023

    • Section

      001
    • Semester

      Spring 2023
    • Date

      Apr 3 - Apr 24
    • Day

      Monday
    • Time

      6:00PM-9:00PM
      • Online
    • Format

      Online
      • Online
    • Sessions

      4
    • Faculty

      TBA
    • Location

      Instructor Led
Toggle

    • Section

      2
    • Semester

      Fall 2022
    • Date

      Oct 24 - Nov 14
    • Day

      Monday
    • Time

      6:00PM-9:00PM
      • Online
    • Format

      Online
      • Online
    • Sessions

      4
    • Faculty

      Bhupathi, Kent
    • Location

      Instructor Led
    Tuition $600