Putting Data to Work: Analysis of Past, Present and Forecast of Business Course

This course answers the following questions with quantitative models. Candidates will understand the fundamentals of this critical business skill

• How can you put data to work for you?
• How can numbers be used to tell you about present and future of business activities?

Through a series of short lectures, demonstrations, candidates will learn the key ideas with which they can begin to create their own models for an enterprise. Candidates will handle a variety of building blocks that will allow them to start structuring own models.

Course Contents

Day One

• Introduction to Models
  • Course Introduction
  • Definition and Uses of Models, Common Functions
  • How Models Are Used in Practice
  • Key Steps in the Modeling Process
  • A Vocabulary for Modeling
  • Mathematical Functions.

Day Two

• Linear Models and Optimization
  • Introduction to Linear Models and Optimization
  • Growth in Discrete Time
  • Constant Proportionate Growth
  • Present and Future Value
  • Optimization.

Day Three

• Probabilistic Models
  • Introduction to Probabilistic Models
  • Examples of Probabilistic Models
  • Regression Models
  • Probability Trees
  • Monte Carlo Simulations
  • Markov Chain Models
  • Building Blocks of Probability Models
  • The Bernoulli Distribution
  • The Binomial Distribution
  • The Normal Distribution
  • The Empirical Rule.

Day Four

• Regression Models
  • Introduction to Regression Model
  • Use of Regression Models
  • Interpretation of Regression Coefficients
  • R-squared and Root Mean Squared Error (RMSE)
  • Fitting Curves to Data
  • Multiple Regression
  • Logistic Regression.

NOTE: Participants Must Be With Their Computers