I have been teaching following courses in the Department of Statistics and Analytical Sciences at the Kennesaw State University since Fall 2015. My most frequently taught three courses are STAT-1107, STAT-3125, STAT-8020 and student evaluations from at least one section of each of these three courses exceeded all benchmark of student evaluations.  

Graduate Courses:

STAT-8220: Time series and Forecasting. Text Book: Time Series Analysis and Its Application with R examples (3rd Edition) by R. Shumway and D. Stoffer.

STAT-8020: Advanced Programming in SAS. Text Book: SAS Base Prep. Guide and SAS Advanced Prep. Guide.

STAT-7900: Theoretical and Computational Bayesian Methods. Text Book: Bayesian Data Analysis (3rd Edition) by A. Gelman, J. Carlin, H. Stern, and D. Rubin. I have developed this course.

STAT-7900: Home Depot Analytics Shotout. Very big data from Home Depot were analyzed in SAS Grid by applying several Statistical methods.

STAT-7010: Mathematical Statistics I. Text Book: Introduction to Mathematical Statistics (7th Edition) by Robert V. Hogg, Joseph W. McKean, Allen T. Craig.

HMI-8240: Data Mining for Health Management and Informatics. Will teach in Spring 2020. This course is offered under Business School.

Undergraduate Courses:

STAT-4030: Programming in R. Notes will be provided to the class via D2L. No specific text book is required.

MATH-3332: Probability and Inference. Text book: A First Course in Probability (9th Edition) by Sheldon Ross.

STAT-3125: Biostatistics. Text book: Mind on Statistics (4th Edition) by Utts and Heckard.

STAT-1107: Introduction to Statistics. Text Book: Essential Statistics, (1st Edition) by W. Navidi and B. Monk.

STAT-2332: Data Analysis and Probability. Text Book: Introductory Statistics: A Problem Solving Approach-Stephen Kokoska.

STAT-4490: Special Topic (Statistical Learning by Python), Text Book: A concise introduction to programming in Python, 2nd Edition, by Mark J. Johnson. I have developed this course so that our undergraduate students will be benefited. Python has more users than R. Both Industry and academia have high demand for Python.