Diploma Level Course
Business Analytics
The problems faced by decision makers in today’s business environments are extremely complex. Hence, the task of making good decisions is not easy. The answer is in building quantitative models, and this course is designed to help you understand the fundamentals of this critical, foundational, business skill. The business application of statistical methods is the core focus of this course. In that sense, the course builds on the core course in the first year of the program. That basic course focused on the preliminaries of the area. This course highlights a business application and then demonstates an application of a statistical techique to solve that scenario and arrive at the best decisions and insights.
Taught by
Rahul R Marathe
Core Competencies
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What You'll Learn
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At the end of the this course, the students will be able to apply various statistical techniques to solve various business problems.
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Extrapolate using various techniques and with statistical robustness.
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Build data-centric business models.
12-Week Roadmap
Course Structure & Syllabus
For details of standard term assessment timelines and exam structures, visit our Academics page.
WEEK 1
Data dashboarding Insights from data summary
WEEK 2
Can summarizing the data provide insights?
WEEK 3
Do people in different cities prefer different
brand?
WEEK 4
Predicting the stock returns – Regression basics
Reading List
Prescribed Books & References
- SF Robert E Stine and Dean Foster, Statistics for Business: Decision Making and Analysis, Pearson.
- NCT Paul Newbold, William L. Carlson and Betty Thorne, Statistics for Business and Economics, Sixth Edition, Pearson.
- ASW David R. Anderson, Dennis J. Sweeney and Thomas A. Williams, Statistics for Business and Economics, Ninth Edition, Cengage Learning.
- Keller Gerald Keller, Managerial Statistics, 9 Edition, Cengage Learning.
- LR Richard Levin and David Rubin, Statistics for Management, Seventh Edition, Pearson.
Faculty & Experts
About the Instructors