332 Int. J. Quality Engineering and Technology, Vol. 3, No. 4, 2013 Copyright © 2013 Inderscience Enterprises Ltd. A comparative analysis of methodologies of daily metroplex ozone concentration prediction Elizabeth A. Cudney*, Steven M. Corns and Protyusha DasNeogi Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA E-mail: cudney@mst.edu E-mail: corns@mst.edu E-mail: protyusha23@gmail.com *Corresponding author Abstract: This paper compares three methods of predicting the changes in ozone concentration: linear regression, classification and regression tree (CART) analysis, and the T-method. Using linear regression on these results, a linear equation defining the change of the independent variable versus the dependent variables is created. The strength of the relationship is assessed using the R-squared value and adjusted R-squared value. Classification and regression tree analysis uses a tree-building methodology to generate decision rules, using patterns from historical data obtained on both the dependent variable and the independent or ‘predictor’ variables to create a prediction model. The T-method is used to calculate an overall prediction based on the dynamic signal-to-noise ratio to obtain an overall estimate of the true value of the output for each signal member. It was found that for this nearly directly correlated dataset the T-method performed comparably to linear regression and was a better predictor than the CART method. Keywords: T-method; prediction; linear regression method; CART; ozone concentration; R-squared values; adjusted R-squared values. Reference to this paper should be made as follows: Cudney, E.A., Corns, S.M. and DasNeogi, P. (2013) ‘A comparative analysis of methodologies of daily metroplex ozone concentration prediction’, Int. J. Quality Engineering and Technology, Vol. 3, No. 4, pp.332–347. Biographical notes: Elizabeth A. Cudney is an Assistant Professor in the Engineering Management and Systems Engineering Department at Missouri University of Science and Technology. She received her BS in Industrial Engineering from North Carolina State University, Master of Engineering in Mechanical Engineering and Master of Business Administration from the University of Hartford, and her Doctorate in Engineering Management from the University of Missouri – Rolla. In 2010, she was inducted into the ASQ International Academy for Quality. She received the 2008 ASQ A.V. Feigenbaum Medal and the 2006 SME Outstanding Young Manufacturing Engineering Award. She is an ASQ Certified Quality Engineer, Manager of Quality/Operational Excellence, and Certified Six Sigma Black Belt. She is a member of the ASEE, ASEM, ASME, ASQ, IIE, SAE, and the Japan Quality Engineering Society (JQES).