QTM1000

Qm For Business Analytics I

QTM1000 Quantitative Methods for Business Analytics I
4 Credits
The course introduces the necessary core quantitative methods that are prerequisites to follow-on courses in QTM and in Babson's integrated core business offerings. Statistical software and the use of spreadsheets are integrated throughout so that students better comprehend the importance of using modern technological tools for effective model building and decision-making. About two thirds of the course is data-oriented, exposing students to basic statistical methods, their conceptual underpinning, such as variability and uncertainty, and their use in the real world. Topics include data collection, descriptive statistics, elementary probability rules and distributions, sampling distributions, and basic inference. The last third of the course is dedicated to selected non-statistical quantitative techniques applied to business models. Topics include curve fitting, differential calculus applications to non-linear optimization, and introduction to the time value of money.

Prerequisites: None

  • Program: Undergraduate
  • Division: Mathematics, Analytics, Science and Technology
  • Level: Foundation Liberal Arts (UGrad)
  • Course Number: QTM1000
  • Number of Credits: 4