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K-State Olathe

Mark Sorell

Mark Sorell

Mark Sorell is a graduate faculty associate in Kansas State University's statistics department. In spring 2016, he began teaching STAT 703: An Introduction to Statistical Methods for the Sciences course at the Kansas State University Olathe campus. 

Sorell is an applied statistician with more than 27 years of experience in private industry and government. He has instructed hundreds of students, technicians, engineers and managers in many different statistics courses.

Prior to joining Kansas State University, he taught as an adjunct professor for the University of New Mexico and as a graduate teaching assistant while studying for his master's degree at Kansas State University.

Sorell worked in the semiconductor industry at Intel Corp. for 23 years, where he supported numerous departments at the corporate headquarters and its development and manufacturing sites. At Intel, he has taught Introduction to Statistics, Statistical Process Control Monitoring, Design of Experiments, Data Mining Techniques, Data Visualization and Graphics, Using Statistical Analysis Software packages (SAS, JMP), Time Series Analysis, Reliability and Part Lifetime Analysis, Metrology System Analysis, and other courses.

After he left Intel, Sorell worked for Hallmark Cards in the Consumer Research and Marketing Division alongside numerous MBAs as well as qualitative and quantitative analysts for three years.  

In 2015, he joined the U.S. Department of Agriculture's Office of the Inspector General helping to start up a newly formed Office of Data Sciences. In this role, Sorell conducts data analysis to help identify fraud, waste and abuse in USDA programs. 

He is a long time member of the American Statistical Association and past vice president and president of its Albuquerque-Santa Fe chapter. He graduated with bachelor's and master's degrees in statistics from Kansas State University. He lives in Olathe with his wife, Traci, and young son, Carlos.

Education

B.S., Statistics, Kansas State University

M.S., Statistics, Kansas State University

Interests and Expertise

  • Applied statistics