Pre-Business school statistics

ABOUT THE COURSE:This course equips incoming business school students with the statistical thinking and analytical tools essential for success in an MBA program. Focused on real-world business scenarios, it emphasizes practical applications over theory. Students will learn how to interpret data, assess uncertainty, model, forecast, and make data-driven decisions across marketing, finance, and operations. No prior background in statistics is required—just curiosity and a willingness to think quantitatively.INTENDED AUDIENCE: An undergraduate in any field who is interested in pursuing an MBA. Student should have an inclination towards data analytics.INDUSTRY SUPPORT: Companies across areas who work on data driven decision making, modelling, analytics etc.

Syllabus

Week 1:Introduction to business statistics and decision-making, types of data, measures of central tendency, measures of dispersion, business case study.
Week 2:Probability and distributions, binomial and normal distributions, central limit theorem and its importance, business application.
Week 3:Inferential statistics, sampling techniques and biases, confidence intervals and hypothesis testing, p-values, type I and type II errors, business case study.
Week 4:Further topics in predictive modelling, correlation, regression, logistic regression etc., final case study.