469 Jon M. Huntsman Hall 3730 Walnut Street Philadelphia, PA 19104
Research Interests: functional data analysis, high dimensional inference, large-scale multiple testing, nonparametric function estimation, statistical decision theory, wavelet methodology and applications
The 2008 COPSS Presidents’ Award, Committee of Presidents of Statistical Societies
Medallion Lecturer, Institute of Mathematical Statistics, 2009
Fellow of the Institute of Mathematical Statistics (IMS).
Academic Positions Held
Wharton: 2000-present (named Dorothy Silberberg Professor, 2007).
Previous appointment: Purdue University
This course covers Elements of (non-measure theoretic) probability necessary for the further study of statistics and biostatistics. Topics include set theory, axioms of probability, counting arguments, conditional probability, random variables and distributions, expectations, generating functions, families of distributions, joint and marginal distributions, hierarchical models, covariance and correlation, random sampling, sampling properties of statistics, modes of convergence, and random number generation. Two semesters of calculus (through multivariate calculus), linerar algebra, or permission of the instructor to enroll.
STAT111 - INTRODUCTORY STATISTICS
Introduction to concepts in probability. Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. The use of the JMP statistical package.
STAT430 - PROBABILITY
Discrete and continuous sample spaces and probability; random variables, distributions, independence; expectation and generating functions; Markov chains and recurrence theory.
STAT431 - STATISTICAL INFERENCE
Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 101 and 102.
STAT510 - PROBABILITY
Elements of matrix algebra. Discrete and continuous random variables and their distributions. Moments and moment generating functions. Joint distributions. Functions and transformations of random variables. Law of large numbers and the central limit theorem. Point estimation: sufficiency, maximum likelihood, minimum variance. Confidence intervals.
STAT915 - NONPARAMETRIC INFERENCE
Statistical inference when the functional form of the distribution is not specified. Nonparametric function estimation, density estimation, survival analysis, contingency tables, association, and efficiency.
STAT972 - ADV TOPICS IN MATH STAT
A continuation of STAT 970.
STAT991 - SEM IN ADV APPL OF STAT
This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.