Teaching

Teaching undergraduate statistics and data analytics is a central part of my academic identity. I am committed to fostering critical thinking, collaboration, and practical application of statistical reasoning, especially for students from diverse academic backgrounds. My teaching emphasizes conceptual understanding over rote memorization, integrates technology and real-world data, and encourages active engagement. I aim to guide students not only to master statistical theory but also to develop analytical reasoning skills, confidence, and the ability to apply knowledge to real-world problems.

Teaching Experience at the University of Dayton

• MTH 412 Probability & Statistics II (SP 26)

MTH 412 is a required course for students pursuing the BS in Applied Economical Mathematics or the BS in Statistics. It serves as a continuation of MTH 411, providing a rigorous introduction to bivariate distributions of random variables, transformations of random variables, sampling distributions, and methods of statistical inference, including estimation and hypothesis testing. 

• MTH 367 Statistical Methods I (FA 25)

MTH 367 is an applied statistical course for students who are not math majors. The course introduces statistical methods with less emphasis on formulas and calculations and more on their application. As part of the course, students have the opportunity to work on projects and use statistical software. Math majors enroll in MTH 411 instead of MTH 367. 

• MTH 209 Data Manipulation and Management (SP 25, FA 24, SP 24)

MTH 209 is a course in the data analytics minor. The main objective of this course is to demonstrate knowledge of technical terms, methods, programming skills, and tools for data manipulation, data management, statistical computing, and data visualization. 

• MTH 369 and MTH 543 as a combined course (FA 24, FA 23)

  • MTH 369 Regression for Data Analytics: a course in the data analytics minor

  • MTH 543 Linear Models: MS in Applied Mathematics program

  • Both courses provide a comprehensive understanding of different regression analysis methods and hands-on experience with statistical software to analyze real data. 

• MTH 208 Exploratory Data Analysis (EDA) (SP 23)

MTH 208 is a new course under the data analytics minor that was offered for the first time in Spring 2023. This course provides an introduction to essential data exploration skills within the context of data analytics.          

• MTH 207 Introduction to Statistics (SP 26, FA 25, SP 25, FA 24, SP 24, FA 23,  SP 23, FA 22, SP 22, FA 21)

MTH 207 is a CAP mathematics course aimed at non-science and engineering technology majors. This course provides an introduction to basic statistical concepts with less emphasis on formulas and calculations and a greater emphasis on their application. 

•  MTH 411 Probability & Statistics I (FA 22)

MTH 411 is a required course for students pursuing the BA in Mathematics or the BS in Applied Economical Mathematics or the BS in Statistics, as well as preservice high school teachers with a concentration in integrated mathematics. It is also an elective for students pursuing the BS in Mathematics.

Teaching Experience at Central Michigan University

• STA 282QR Introduction to Statistics (FA 20, SP 20, FA 19)

• MTH 105 Intermediate Algebra (SP 19, FA 18)

• STA 382QR Elementary Statistical Analysis (SP19)

Teaching Experience at the University of Peradeniya, Sri Lanka

• MT 121 Mathematics for Art/Commerce Students I (2012)

• MT 315 Operations Research III (2012)

• Honors Thesis Projects

  • During FA 25 - SP 26, Constructing an Extreme Value Model to Predict Municipal Financial Risk Based on Corporate Bankruptcy by Megan Coyne.

    • Poster presentation at the Electronic Undergraduate Statistics Research Conference (eUSR) 2025

• MTH 480 Mathematics Capstone Projects

  • In SP 25, Predicting the Home Field Advantage in the NFL by Samuel Limbert.

  • In SP 25, Numbers Don't Lie: Forecasting the NBA Champion with Machine Learning by Jonah Mergler.

  • In FA 24, How MLB’s New Rules Have Impacted the Game by Margot Houser.

  • In SP 24, Gamma Exponentiated Burr XII Distribution and its Applications by Hannah Wabel.

  • In FA 23, Beta-Chen Distribution and its Applications by Evan Smyjunas.

  • In SP 23, Exponentiated Kumaraswamy-Burr Distribution and its Applications by Alexander Griffiths.

Training Sessions Organized by the Center for Online Learning at the University of Dayton

• Canvas Assessment Building

• Canvas Essentials (Introductory training session)

• Advancing Teaching & Learning Scholars (ATLS) Core Program - Completed (Spring 2024)

  • • Core Session 1: Who are Our Students?

    • Core Session 2: Supporting Students In and Beyond the Classroom 

    • Core Session 3: Using Educational Technologies at UD to Support Learning 

    • Core Session 4: Driving Student Success

    • Core Session 5: Engaging Students in a Learner-Centered Classroom 

    • Core Session 6: How Do You Know If Students Are Learning?

    • Core Session 7: Inclusive Pedagogy

    • Core Session 8: Why Do We Teach?

• Gradescope New User Training

• Evaluate Before You Duplicate

• Creating Graphics to Enhance Your Teaching

Teaching Internship (Spring 2019)

Department of Statistics, Actuarial and Data Sciences, Central Michigan University

Course: STA 382QR Elementary Statistical Analysis

Supervisor: Prof. Felix Famoye

Courses on Mathematics Education

Department of Mathematics, Central Michigan University

• MTH 762 A Survey of Research in Collegiate Mathematics Education (Spring 2018)

• MTH 761 Methods for Teaching College Mathematics (Fall 2017)

• Guest speaker for RPL 518 – Research and Philosophy in RPL course by Dr. Kyunghee Lee, A Presentation on Basic Statistics and Using SPSS statistical software, Department of Recreation, Parks, and Leisure Services Administration, Central Michigan University, Mount Pleasant, MI. Oct 2017.

• Guest speaker for RPL 518 - Research and Philosophy in RPL course by Dr. Kyunghee Lee, A Workshop on Using SPSS Statistical Software, Department of Recreation, Parks, and Leisure Services Administration, Central Michigan University, Mount Pleasant, MI. Feb 2017.

• Research Appreciation Week Workshop, How Can the Applied Research Lab (ARL) Help You with Your Research, Indiana University of Pennsylvania, Indiana, PA. 2014.