My primary interests are in applied statistics and the philosophy of statistics. Most of my work has been in statistical methods for photovoltaic (solar cell) performance modeling. I have also worked on applications for residential building energy analysis and on a consulting team that provides statistical litigation support. In addition to math and statistics, I am also interested in a number of areas in philosophy, including ethics, philosophy of science, and phenomenology.
APPM 3310  Matrix Methods and Applications
Primary Instructor

Spring 2018
Introduces linear algebra and matrices with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses vector space concepts, decomposition theorems, and eigenvalue problems. Degree credit not granted for this course and MATH 2130 and MATH 2135.
APPM 4520  Introduction to Mathematical Statistics
Primary Instructor

Fall 2018 / Fall 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Same as STAT 5520 and MATH 4520 and MATH 5520.
APPM 4570  Statistical Methods
Primary Instructor

Spring 2018
Covers basic statistical concepts with accompanying introduction to the R programming language. Topics include discrete and continuous probability laws, random variables, expectation and variance, central limit theorem, testing hypothesis and confidence intervals, linear regression analysis, simulations for validation of statistical methods and applications of methods in R. Same as APPM 5570.
APPM 5520  Introduction to Mathematical Statistics
Primary Instructor

Fall 2018 / Fall 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Department enforced prerequisite: one semester calculusbased probability course, such as MATH 4510 or APPM 3570. Same as STAT 4520 and MATH 4520 and MATH 5520.
APPM 5570  Statistical Methods
Primary Instructor

Spring 2018
Covers basic statistical concepts with accompanying introduction to the R programming language. Topics include discrete and continuous probability laws, random variables, expectation and variance, central limit theorem, testing hypothesis and confidence intervals, linear regression analysis, simulations for validation of statistical methods and applications of methods in R. Same as APPM 4570.
MATH 4520  Introduction to Mathematical Statistics
Primary Instructor

Fall 2018 / Fall 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Same as MATH 5520 and STAT 4520 and STAT 5520.
MATH 5520  Introduction to Mathematical Statistics
Primary Instructor

Fall 2018 / Fall 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Department enforced prerequisite: MATH 4510 or MATH 5510 or APPM 3570. Same as MATH 4520 and STAT 4520 and STAT 5520.
STAT 3400  Applied Regression
Primary Instructor

Spring 2019
Introduces methods, theory, and applications of linear statistical models, covering topics such as estimation, residual diagnostics, goodness of fit, transformations, and various strategies for variable selection and model comparison. Examples will be demonstrated using statistical programming language R.
STAT 4010  Statistical Methods and Applications II
Primary Instructor

Spring 2019
Expands upon statistical techniques introduced in STAT 4000. Topics include modern regression analysis, analysis of variance (ANOVA), experimental design, nonparametric methods, and an introduction to Bayesian data analysis. Considerable emphasis on application in the R programming language. Same as STAT 5010.
STAT 4700  Philosophical and Ethical Issues in Statistics
Primary Instructor

Fall 2019
Introduces students to philosophical issues that arise in statistical theory and practice. Topics include interpretations of probability, philosophical paradigms in statistics, inductive inference, causality, reproducible, and ethical issues arising in statistics and data analysis. Same as STAT 5700.
STAT 5010  Statistical Methods and Applications II
Primary Instructor

Spring 2019
Expands upon statistical techniques introduced in STAT 4000. Topics include modern regression analysis, analysis of variance (ANOVA), experimental design, nonparametric methods, and an introduction to Bayesian data analysis. Considerable emphasis on application in the R programming language. Same as STAT 4010.
STAT 5700  Philosophical and Ethical Issues in Statistics
Primary Instructor

Fall 2019
Introduces students to philosophical issues that arise in statistical theory and practice. Topics include interpretations of probability, philosophical paradigms in statistics, inductive inference, causality, reproducible, and ethical issues arising in statistics and data analysis. Same as STAT 4700.