Yusuf K. Bilgiç

Assistant Professor
South Hall 324A

Yusuf K. Bilgiç has been a member of the Geneseo faculty since 2012. 

Did you know UP-STAT 2018 Conference is in Rochester (UR), April 20-21?


Office hours and course websites

Curriculum Vitae


  • Ph.D. in Statistics, Western Michigan University, 2012

  • M.A. in Teaching Math, Western Michigan University, 2008


  • Bilgic, Y., Morgan, B., Petakos, K. 2017. Using ​ ​Sociocultural ​ ​Theory ​ ​and ​ ​Group ​ ​Interviews ​​to ​ ​Support ​ ​Students' ​ ​Understanding ​ ​of Concepts ​ ​from ​ ​Conditional ​ ​Probability. Submitted.

  • Urso, A., Bilgic Y. K., Reuter, G., Riccomini, P. J. 2017. Instructional Supports for Struggling Students in Probability and Statistics Instruction. Submitted.

  • Bilgic Y. K., McKean J. W., Kloke J. D., and Abebe A. Iteratively reweighted generalized rank-based methods for hierarchical mixed models. In progress.

  • Abebe Asheber, McKean Joseph W., Kloke John D., and Bilgic Yusuf K. 2016. Iterated Reweighted Rank-Based Estimates for GEE Models. Robust Rank-Based and Nonparametric Methods, Volume 168 of the Series Springer Proceedings in Mathematics & Statistics, pp 61-79, Book Chapter. Liu R. and McKean J. (Eds.), Springer International Publishing.

  • LaVigne* N., Bilgic Y. 2015. Robust Estimators In Fuzzy Logic Cellular-Automata Salt And Pepper Noise Filtering. International Journal of Computers and Technology. Vol 15, No 1.

  • Bilgic, Y. K., J., Susmann, H., McKean. 2014. rlme: An R Package for Rank-Based Estimation and Prediction in Random Effects Nested Models. URL R package version 0.4.1

  • Jon D. Davis, Dustin O. Smith, Abhik R. Roy, Yusuf K. Bilgic. 2014. Reasoning-and-proving in algebra: The case of two reform-oriented U.S. textbooks, International Journal of Educational Research, Volume 64, 2014, Pages 92-106, ISSN 0883-0355,

  • Bilgic, Y. K., Susmann, H. 2013. rlme: An R Package for Rank-Based Estimation and Prediction in Random Effects Nested Models. The R Journal, 5(2):71?80.

  • Bradley, C., DeBose C. H., Terpstra, J. T. and Bilgic, Y. K. 2012. Postadoption Services Utilization Among African American, Transracial, and White American Parents: Counseling and Legal implications. The Family Journal. October 2012 Vol. 20 No. 4 392-398.

  • Bilgic, Y. K. Rank-Based Estimation and Prediction for Mixed Effects Models in Nested Designs. Ph.D. Thesis. 2012. WMU.

More About Me

Research Interests

Probability, Statistics and Data Science (PSDS) education for grades 6 to 16; Nonparametric modeling and estimate; Modeling, estimation, prediction and testing in linear designs with dependent error structures using robust nonparametric methods, i.e. rank-based statistical modeling of hierarchical/nested designs;


Developing Machine Learning (ML) course and Data Science materials; Expecting an external grant on a collaborative proposal in PSDS; Working with students in some research topics in PS and ML;


  • MATH 160: R/Elements of Chance

    This course will help students learn how to think about statistics and probability, how to identify the tools needed to study a particular problem and how to read and critically evaluate quantitative information presented in the media. The course format involves extensive reading and discussion of newspaper and journal articles, computer activities, writing assignments, and student projects. (Those who have completed MATH 242, 260, or 360 may not enroll in this class for credit. Those majoring in mathematics may only receive free elective credit for the course.) Prerequisites: Three years of high school mathematics including intermediate algebra. Offered every fall

  • MATH 221: R/Calculus I

    Topics studied are limits and continuity; derivatives and antiderivatives of the algebraic and trigonometric functions; the definite integral; and the fundamental theorem of the calculus. Prerequisites: MATH 112 or Precalculus with trigonometry or the equivalent. Offered every semester

  • MATH 341: Probability &AppliedStatistics

    Topics include probability definitions and theorems; discrete and continuous random variables including the binomial, geometric, Poisson, and normal random variables; and the applications of statistical topics such as sampling distributions, estimation, confidence intervals, and tests of hypothesis. Both the theory and applications of probability will be included with applications of statistics. A student may not receive major credit for both MATH 341 and MATH 360. MATH 341 does NOT serve as a prerequisite for MATH 361. Prerequisite: MATH 223 or permission of instructor. Offered every spring