Regression and Time Series Analysis

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Regression and Time Series Analysis

This course is designed for students who have taken Data Society’s Introduction to R and Visualization course or have a good knowledge of R programming. This 3 ½ hour course teaches students how to apply advanced regression and time series models to accurately predict business trends and demand.

Course Objectives

  • Identify the most important predictive variables in a model
  • Quantify qualitative variables and incorporate them in a predictive model
  • Build predictive models to anticipate trends and demand
Prerequisites: Intro to R View syllabus
Instruction: 3 hrs 30 min
Practice: 20 – 25 hrs

Dr. Kaska Adoteye

Kaska Adoteye has a PhD in Applied Mathematics from NC State University. He is passionate about using math and statistics to solve real world problems with a maximum impact. He has formulated, tested, and coded models to profitably trade stocks for an investment firm, as well as to create predictive models to examine the effects of various toxicants on populations of biological organisms. He is currently developing an artificial intelligence engine to help secure cyber networks.