About this courseSkip About this course
Statistics is a versatile discipline that has revolutionized the fields of business, engineering, medicine and pure sciences. This course is Part 2 of a 4-part series on Business Statistics, and is ideal for learners who wish to enroll in business programs. The first two parts cover topics in Descriptive Statistics, whereas the next two focus on Inferential Statistics.
Spreadsheets containing real data from diverse areas such as economics, finance and HR drive much of our discussions.
In Part 2, we use the language of probability to examine the underlying distributions of random variables. We model real-life phenomena using known variables such as Binomial, Poisson and Normal. We 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 analyze using a spreadsheet. This is a natural setting for R, an advanced statistical programming platform. We incorporate helpful tutorials to get learners acquainted with the platform.
What you'll learnSkip What you'll learn
- To use spreadsheets to analyze larger datasets
- To pose pertinent business questions of datasets and to answer them
- To describe a random variable in probabilistic terms and derive parameters such as mean and variance
- To draw a simple random sample from a population
- To model business phenomena with known random variables such as Binomial, Poisson and Normal
- To simulate variables that follow a prescribed distribution
Meet your instructors
Pursue a Verified Certificate to highlight the knowledge and skills you gain$50 USD
Official and Verified
Receive an instructor-signed certificate with the institution's logo to verify your achievement and increase your job prospects
Add the certificate to your CV or resume, or post it directly on LinkedIn
Give yourself an additional incentive to complete the course
Support our Mission
EdX, a non-profit, relies on verified certificates to help fund free education for everyone globally