Statistics for Business – II

Course Information

Course Length : 7 Weeks
Estimated Efforts : 3 – 4 hours/week

Statistics is a versatile discipline that has revolutionised the fields of business, engineering, medicine, and pure sciences. This IIMBx course Statistics for Business – II is Part 1 of the two-part series on Business Statistics and is ideal for learners who wish to enrol in business programs. These two courses cover topics in Descriptive Statistics. Spreadsheets containing real data from diverse areas such as economics, finance, and HR drive much of the discussions that are part of the course.

In the previous part part, Statistics for Business – I, you would have already learnt about the multiple ways to describe large datasets, numerically as well as visually, and also the tools and techniques available to solve problems.

In this part, Statistics for Business – II, the focus is on the use of the language of probability to examine the underlying distributions of random variables. You will model real-life phenomena using known variables such as Binomial, Poisson and Normal, and learn how to simulate data that are distributed according to these variables.

We shall take up datasets that have over a million rows which makes it difficult to analyse using a spreadsheet. This forms a natural setting for R, an advanced statistical programming platform. We will provide you with useful tutorials to get yourself acquainted with the R platform.

Professor Shankar Venkatagiri

Course Instructor
Information Systems
Indian Institute of Management Bangalore (IIMB)

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Course Syllabus

Week 1: Introduction to course

Introduction
Recap
Entrepreneurship Demo

Week 2: R Tutorial - I

In this week, you will learn to define and cite examples of various elements in the balance sheet related to:

Installing R & RStudio
Basics of RStudio

Week 3: R Tutorial - II

Writing programs in RStudio & HR Demo

Week 4: Standard Variables - I

Uniform Distribution
Binomial Distribution
Poisson Distribution

Week 5: Standard Variables - I

Exponential Distribution

Week 6: Simulation

Monte Carlo Simulation

Week 7: Normal Distribution

Properties
Basic Application

Learning Outcome

After completing this two-part series, the participants should be able to:

Analyse larger datasets using spreadsheets
Create pertinent business questions to examine datasets with and derive answers
Describe a random variable in probabilistic terms and derive parameters such as mean and variance
Draw a simple random sample from a population
Model business phenomena with known random variables such as Binomial, Poisson, and Normal
Simulate variables that follow a prescribed distribution