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Master of Science in Applied Statistics (MSAS)

The Master of Science in Applied Statistics (MSAS) Program at Kennesaw State University is a professional degree program which seeks to prepare a diverse student body to utilize cutting-edge statistical methods to draw valid and meaningful inferences from business, industry, government and health services data. Using a variety of commercial software, graduates are expected to analyze real-world data appropriately and communicate their findings effectively.

The MSAS degree is a 22-month early evening program designed for professionals or students with undergraduate degrees in the sciences or business. Course titles include:

  • Introduction to Mathematics for Statistics
  • Mathematical Statistics
  • Statistical Computing and Simulation
  • Statistical Methods
  • Advanced Programming in SAS
  • Quality Control and Process Improvement
  • Applied Experimental Design
  • Design of Human Studies
  • Six Sigma Problem Solving
  • Applied Regression Analysis
  • Time Series Analysis
  • Applied Longitudinal Data Analysis
  • Data Mining
  • Applied Categorical Data Analysis
  • Applied Multivariate Methods
  • Applied Topics in Binary Classification
  • Applied Analysis Project

An emphasis of the MSAS program is in applied statistical methods used in industry and government for process and quality improvement. A key focus is the continuous training and practice using Six Sigma methodology of process improvement. These techniques are in demand in industry due to the cost savings typically resulting from process improvement activities. Upon completion of program, students will be able to:

  • Apply appropriate statistical methods to solve problems
  • Analyze data using several statistical packages
  • Identify opportunities for quality and productivity improvement
  • Establish process control systems
  • Lead problem-solving teams
  • Communicate project results orally and in writing

< View MSAS Program Description in KSU Graduate Catalog >

Page last updated: March 19, 2014

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