Dr. Galit Shmueli

Dr. Galit Shmueli Dr. Galit Shmueli is a Distinguished Professor of the Institute of Service Science, College of Technology Management at National Tsing Hua University, Taiwan.  Previous academic appointments include the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics and Information Systems at the Indian School of Business, Hyderabad, and Associate Professor of Statistics in the Department of Decision, Operations & Information Technologies at the Smith School of Business, University of Maryland.  Dr. Shmueli's research has been published in the statistics, information systems, and marketing literature.

Education:

BA Statistics & Psychology, Haifa University

MSc Statistics, Technion - Israel Institute of Technology

PhD Statistics, Technion - Israel Institute of Technology

Areas of Expertise:

Forecasting

Data Visualization

Statistical Modeling

Publications:

Co-author, Getting Started with Business Analytics: Insightful Decision Making (Taylor & Francis, 2013)

Author, Practical Time Series Forecasting (CreateSpace, 2011)

Author, Practical Acceptance Sampling (2011)

Author, Practical Risk Analysis for Project Planning (CreateSpace, 2011)

Co-author, “Predictive Analytics in Information Systems Research” in MIS Quarterly, 2011

Co-author, Data Mining for Business Intelligence (John Wiley and Sons, 2010)

Co-author, Modeling Online Auctions (John WIley and Sons, 2010)

Author, “To Explain or To Predict?” in Statistical Science, 2010

Co-author, “A Flexible Regression Model for Count Data” in Annals of Applied Statistics, 2010.

Co-author, Statistical Methods in e-Commerce Research (John Wiley and Sons, 2008)

Co-author, "Consumer Surplus in Online Auctions" in Information Systems Research, 2008.

Co-author, "Modeling Price Dynamics in eBay Auctions Using Principal Differential Analysis" in Journal of the American Statistical Association, 2008.

Website links:

Galit Shmueli

Courses:
Forecasting Analytics
Interactive Data Visualization
Predictive Analytics 1 - Machine Learning Tools
Predictive Analytics 2 - Neural Nets and Regression
Predictive Analytics 3: Dimension Reduction, Clustering and Association Rules

Instructor at Statistics.com since April 2009



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