People » Morgan C Wang


Education

  • Ph.D Statistics, 1991 – Iowa State University
  • M.S Math/Computer Science, 1986 – Mankato State University
  • B.S Management Science, 1977 – National Chiao-Tung University

Research and consulting include: web-mining, data mining, meta-analysis, non-linear time series in traffic prediction, probabilistic theory for fracture mechanics,corrosion pittings analysis and computation methods for multivariate data analysis.

  • Marcella Bush, Charles Dziuban, Patsy Moskal, and Morgan C. Wang (accepted), “Student Success in Online Learning”, 2004.
  • Technical Report: Tree-Augmented Regression (TAR) Analysis
  • Morgan C. Wang, Charles D. Dziuban, and Patsy D. Moskal (2001), “A Web-based Survey System for Distributed Learning Impact Evaluation” The Internet and Higher Education, Vol. 2, No. 2, 211-220
  • Ahn Y., Nicholson, D. W., and Morgan C. Wang (2000), “Inverse Method for Identifying the Underlying Crack Distribution in Plates with Random Strength,” Journal of ACTA MECHANICA, No. 144 (3-4), pp 137-154.
  • P. D. Angelo, Al-Deek, and Morgan C. Wang (1999), “Travel Time Prediction for Freeway Corridors,” Journal of Transportation Research Board, No. 1676, pp 184-191.(1999)
  • Jennifer E. Irvin, Clint A. Bowers, Michael E. Dunn, and Morgan C. Wang, “Efficacy of Relapse Prevention: A Meta-Analytic Review,” Journal of Consulting and Clinical Psychology, Vol. 67, No. 4,563-570.(1999)
  • Morgan C. Wang and Brad J. Bushman, “Using Normal Quantile Plots in Meta-Analysis,” Psychological Methods, 2, 131-142(1999).
  • Morgan C. Wang and Brad J. Bushman, “Integration Results through Meta-Analytic Review Using SASâ Software,” SAS Institute, January 1, 1999.
  • H. M. al-deek, P. D. Angelo, Morgan C. Wang, “Travel Time Prediction with Non-linear Time series,” ASCE Journal of Transportation Engineering, Vol.122,
  • Morgan C. Wang and Willian J. Kennedy, “Nuverical Methods for Use in Preparing High Quality Statistical Tables,” Statistics if Quality, 333-342(1997).
  • Brad J. Bushman and Morgan C. Wang, “A Procedure for Combining Sample Standardized Mean Differences and Vote Counts to Obtain an Estimates and a Confidence Interval for the Population Standardized Mean Difference,” Psychological Methods, vol. 1, pp. 66-80 (1996).
  • Morgan C. Wang and William J. Kennedy, “A Self-validating Numerical Method for Computation of Central and Non-Central F Probabilities and Percentiles,” Statistics and Computing, vol. 5, pp. 155-163 (1995).
  • Brad Bushman and Morgan C. Wang, “Vote-Counting Procedures for Obtaining an Estimate and Confidence Interval for the Population Coefficient of Correlation,” Psychological Bulletin, vol. 117, pp. 530-546 (1995).
  • Mary Ann Evans, Myrna Whigham, and Morgan C. Wang, “The Effect of a Role Model Project Upon the Attitudes of Ninth Grade Science Students,” Journal of Research in Science Teaching, vol. 32, pp. 195-204 (1995).
  • Morgan C. Wang and William J. Kennedy, “Self-validating Computations of Probabilities and Percentiles for Selected Central and Non-Central Univariate Probability Functions,” Journal of the American Statistical Association, vol. 89, pp. 878-887 (1994).
  • Morgan C. Wang and Ned Silver, “A Microsoft FORTRAN 77 Program for Determining the Confidence Interval Around the Estimate of the Population Correlation Coefficient for the Vote-Counting Method,” Educational and Psychological Measurement, vol. 54, pp. 110-114 (1994).
  • Morgan C. Wang and William J. Kennedy, “A Numerical Method for Accurately Approximating Multivariate Normal Probabilities,” Computational Statistics and Data Analysis, vol. 13, pp.197-210 (1992).
  • Morgan C. Wang and William J. Kennedy, “Comparison of Algorithms for Bivariate Normal Probabilities Over a Rectangle Based on Self-Validating Result from Interval Analysis,” Journal of Statistical Computation and Simulation, vol. 37, pp. 13-25 (1990).

FALL 2016:

  • STA 5703.055:   Data Mining Methodology I
  • STA 6714.055:   Data Preparation

Office hours  – 1 hour before class or by appointment

  • Monday

    • 4:30 PM to 5:30 PM
  • Tuesday

    • Not Available
  • Wednesday

    • 4:30 PM to 5:30 PM
  • Thursday

    • Not Available
  • Friday

    • Not Available