Background

As a passionate and enthusiastic student many years ago, I learned Statistics with a highly technical and mathematical approach. Almost all my statistical inference classes started with an assumption that a sample of size n is a point in an n-dimensional Euclidean space!


Many years later, when I came to teach Statistics to undergraduate and graduate students at a business school, I realized all business students neither are nor need to be technical and quantitative-minded. So I started researching how I should teach Statistics intuitively to these students so they can apply it to solve real-life problems and make better business decisions.


This course is the outcome of my research for the last few years. It avoids the mathematical approach and extensive use of formulas. Instead focuses on statistical intuitions and the creation of mental models of uncertainty. In this course, we use the R language and an R code generator, Statsbuddy, that I created to focus more on 'why' and 'what', instead of 'how', of Statistics.

Learning Objectives

After completion of this course, students should be able to:

  • Intuitively understand and apply the various statistical concepts to searching for optimum business decisions

  • Utilize statistical thinking to conduct data analysis, interpret the statistical results, and make fact-based decisions

  • Understand benefit of the most popular computational software (such as R) to facilitate the computational process

Course curriculum

    1. Introduction to Statistics - Part 1

    2. Introduction to Statistics - Part 2

    3. Introduction to Statistics - Part 3

    4. Introduction to Statistics - Part 4

    1. Basics of R Language

    2. Using R Language

    1. Descriptive Statistics - Part 1

    2. Descriptive Statistics - Part 2

    3. Descriptive Statistics - Part 3

    4. Descriptive Statistics - Quiz

    1. Theory of Probability - Part 1

    2. Theory of Probability - Part 2

    3. Theory of Probability - Part 3

    4. Theory of Probability - Part 4

    5. Theory of Probability - Part 5

    6. Theory of Probability - Quiz

    1. Random Variables & Probability Distributions - Part 1

    2. Random Variables & Probability Distributions - Part 2

    3. Random Variables & Probability Distributions - Part 3

    4. Random Variables & Probability Distributions - Quiz

    1. Normal Distribution - Part 1

    2. Normal Distribution - Part 2

    3. Normal Distribution - Part 3

    4. Normal Distribution - Quiz

About this course

  • Free
  • 52 lessons
  • 7.5 hours of video content

Instructor(s)

Abhimanyu Gupta

Instructor

Abhimanyu Gupta is an Instructor of Data Science at Richard A. Chaifetz School of Business at Saint Louis University since 2017. He did his Master of Statistics (M.Stat.) from the Indian Statistical Institute and is currently a Ph.D. student at Ghent University, Belgium, since 2017. Before coming to academics, Abhi worked as a Project Manager in the Information Technology industry for 17 years. In 2018, Abhi created a code-generation tool, statsbuddy.net, to help non-technical business students take advantage of advanced data science tools and techniques. The tool is currently used by thousands of students inside and outside Saint Louis University. Abhi received the Emerson Excellence in Teaching Award in 2021. He is also the recipient of the Graduate Faculty of the Year awards for two consecutive years, 2021 and 2022, and the Beta Gamma Sigma Outstanding Teacher Award in 2023.