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About This Course
Discrete Probability Distributions
Continuous Probability Distributions
Statistical Sampling and Regression

PreMBA Analytical Methods
Orientation: About This Course

About This Course

To the incoming student, mathematics is a daunting aspect of the MBA program. If you spent your undergraduate career in the liberal arts, or if you are entering the program after several years in the workforce, you may worry that you have forgotten the material you will need to succeed in business school.

PreMBA Analytical Methods offers a refresher targeted toward the specific mathematical requirements of the business world. However, beyond refreshing your math skills, this course will help you amplify your analytical skills as you work through the math problems in each section of the course. Analytical skills are critical in business school and in the business world—decision-makers must be able to analyze a complex problem, consider all options, and make the best decision based on the most complete collection of facts. This is not a review of high school or undergraduate mathematics; rather, it is a preview of the analytical methods used daily in the business world.

Learning Outcomes

Completing each section and the associated exercises should provide you with a firm grounding in the mathematical and statistical techniques you'll encounter in your MBA program. Becoming familiar with this material should give you the tools you need to master any additional analytical techniques introduced in your MBA program.

After completing PreMBA: Analytical Methods, you should be able to

  • make calculations using algebra, simple calculus, and statistics
  • apply appropriate mathematical and statistical techniques to business problems

Completing This Course

The different sections of this course treat five general topic areas: algebra, precalculus, probability distributions, statistical sampling, and regression. Begin by taking the Preassessment. This will help you identify which topics you should review most closely. For a "crash course" in math and statistics, you can work sequentially through the sections listed in the left margin. Each section features exercises to test your understanding of the different topics. After completing the different sections, take the Postassessment to assess your mastery of the course material.

If you'd like to pursue any of these topics in greater depth, the following are recommended texts:

Haeussler, E. F., Jr., and R. S. Paul. Introductory Mathematical Analysis for Business, Economics, and the Life and Social Sciences. Upper Saddle River, N.J.: Prentice-Hall, 1999.

Bertsimas, D., and R. M. Freund. Data, Models, and Decisions: The Fundamentals of Management Science. Cincinnati, Ohio: South-Western College Publishing, 2000.


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PreMBA Analytical Methods may include the names and publicly available information of certain actual companies, products, and organizations. Any use of such name or such information about a company, product, or organization is solely for educational purposes.

PreMBA Analytical Methods may also use fictitious events, scenarios, and characters that may make reference to fictional companies, products, and organizations, as will be clearly indicated in the course content. Any similarity between these fictional events, scenarios, characters, companies, products, and organizations to actual such events or entities is unintentional and purely coincidental. Likewise, any similarity between such fictional characters and actual persons, living or dead, is also unintentional and purely coincidental.

No part of this course or any educational material contained herein may be reproduced or distributed in any manner without express written permission by the copyright holder.

This course may contain video clips of persons expressing opinions on certain topics. The opinions expressed are those of the person expressing the opinions and not those of Columbia University. No representation is made that any such opinions are accurate or complete. Columbia University will not be responsible or liable for claims relating to the opinions. Columbia University does not make any express or implied representations or warranties as to the accuracy or completeness of the opinions, or for statements or errors contained therein, or omissions from them.

This course contains graphic images and animations involving Microsoft Excel. The terms Microsoft and Excel are the property of Microsoft Corporation, and their appearance in this course does not represent any affiliation with or sponsorship of this course or Columbia University.

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