John Draper joins the Department of Management Sciences as a Clinical Assistant Professor. He comes from The Ohio State University’s Department of Statistics, where he served as visiting faculty and taught both graduate and undergraduate courses in statistical theory and application. His teaching experiences at Ohio State also include statistics in business, engineering and sports as well as biostatistics courses for graduate-level students in the College of Public Health and Dentistry.

Draper has a PhD and MS in statistics from Ohio State as well as BS degrees in mathematics and statistics from Florida State University.

His professional experiences include roles as a statistical consultant as well as positions at Battelle Memorial Institute and Cengage Learning. Draper is a member of the American Statistical Association, and the recipient of the Thomas E. and Jean D. Powers Award for Outstanding Teaching Associate.

Draper is a proud alum of The Ohio State University Marching Band (2003-07) and the Florida State University Marching Chiefs (1999-2003). He has also worked closely with the OSUMB in halftime show design since 2006.

Areas of Expertise

  • Business Analytics
  • Sports Analytics
  • Six Sigma methodology
  • Statistical Computing


  • PhD in Statistics, The Ohio State University
  • MS in Statistics, The Ohio State University
  • BS in Mathematics, Florida State University
  • BS in Statistics, Florida State University


  • BUSMGT 2320 - Decision Sciences: Statistical Techniques

    Examination of the use of statistical techniques in managerial decision-making processes; statistical inference, simple and multiple regression, time series. Prereq: Math 1131 (132), or 1151 (152); and Stat 1430 (133); and CSE 1113, or 2111 (200); and Econ 2001.01 (200). Prereq or Concur: Econ 2002.01 (201). Not open to students with credit for 330. This course is available for EM credit.

  • BUSMGT 4242 - Business Sports Analytics

    Analytical techniques and quantitative methods are on the rise in many areas of industry, and, of late, have made their foray into the sports realm. Skills such as critical thinking, mathematical modeling, statistical analysis, predictive analytics and optimization are crucial in the data-centric realm. The class seeks to develop and refine these skills in the business application area of sports. Prereq: Stat 3202, or permission of instructor.

  • BUSMGT 7256 - Tools for Data Analysis

    This course is designed to introduce students to commonly used software programs in data science and improve students' problem solving skills and logical thought processes. Students will be exposed to R, SAS, and SPSS. Prereq: MBA 6271 or 6273.

  • ACCTMIS 6001 - Fundamentals of Accounting Data & Analytics

    Provides an introduction to using large datasets to better understand corporate financial reporting and market behavior. Prereq: Enrollment in Master of Accounting Program.

  • BUSMGT 6400 - Statistics and Data Analysis for Managers

    Students will learn how to work with data, formulate questions, and most importantly, learn comprehensive problem solving techniques to extract and explain pertinent information from data. The course will track the problem solving process from problem formulation to data acquisition/cleaning to data analysis and conclusion to communication of the results. Prereq: Enrollment in the SMB-A program, or permission of instructor.

  • BUSMGT 6222 - Data Analysis for Financial Management Part II

    Introduction to data analysis and statistics for business. Emphasis on achieving an application-oriented understanding of statistical inference and regression analysis and their use in decision making. Part 2 of 2 course sequence. Prereq: Enrollment in MBOE or SMB-Finance Program Course. Concur: 6221. Not open to students with credit for 870.

  • BUSMGT 7334 - Sports Analytics

    Analytical techniques and quantitative methods are on the rise in many areas of industry, and, of late, have entered the sports realm. Students will expand their critical thinking skills, explore the current state of sports analytics, summarize data creatively, improve data-based decision making, and optimize output in real-world situations as well as improve presentation skills to the non-quant. Prereq: Enrollment in SMB-Analytics program, or permission of instructor.

  • BUSMGT 7268 - MBOE Six Sigma Projects

    Six Sigma Project is a supervised DMAIC project executed by the student and with the help of a team in the student's own workplace. A faculty coach supervises and guides the effort and a company sponsor supports the effort. Prereq: Enrollment in MBOE. Not open to students with credit for 811.