The Challenges in Developing an Online Applied Statistics Program: Lessons Learned at Penn State University

Numerous professional fields have an increasing need for individuals trained in statistics and other quantitative analysis techniques. Today there exists great potential to fulfill this need by providing opportunities through online learning. However, to provide a high-quality education for returning adult professionals seeking advanced degrees in applied statistics online, many challenges need to be overcome. Based on our experience developing Penn State University’s online program in applied statistics, we discuss the evolution of the program’s curriculum, recruitment and development of online faculty, and meeting the requirements of students as important areas that require consideration in the development of an online program. We also highlight program evaluation strategies employed to ensure innovation and improvement in online education as cornerstones to a program’s success.     

Urn designs with immigration: Useful connection with continuous time stochastic processes

In this paper we present techniques that allow obtaining joint and marginal distributions of random variables arising in urn designs with immigration. The urn is embedded into a family of continuous time Markov processes. Then the generating function approach is used to obtain distributional results. A randomized version of the inverse sampling is introduced.     

Uniform Distributions on the Integers: A connection to the Bernouilli Random Walk

Associate to each subset of the integers its almost sure limiting relative frequency under the Bernouilli random walk, if it has one. The resulting probability space is purely finitely additive, and uniform in the sense of residue classes and shift-invariance. However, it is not uniform in the sense of limiting relative frequency.