James Marengo Headshot

James Marengo

Professor

School of Mathematics and Statistics
College of Science
Minors Coordinator, Actuarial Science

585-475-6872
Office Hours
Monday 12:30-1:15 in Zoom for Math 251 Monday 1:15-2pm in Zoom for Stat 405 Wednesday 12:30-1:15 in Zoom for Math 251 Wednesday 1:15-2 in zoom for Math 295 Friday 1-3pm in Zoom for Stat 405 (help session)
Office Location

James Marengo

Professor

School of Mathematics and Statistics
College of Science
Minors Coordinator, Actuarial Science

Education

BA, MS, California State University; Ph.D., Colorado State University

585-475-6872

Currently Teaching

MATH-251
3 Credits
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.
MATH-255
3 Credits
This course provides challenging problems in probability whose solutions require a combination of skills that one acquires in a typical mathematical statistics curriculum. Course work synthesizes basic, essential problem-solving ideas and techniques as they apply to actuarial mathematics and the first actuarial exam.
MATH-295
3 Credits
This course develops strategies for solving problems that are chosen from a wide variety of areas in mathematics. Students present solutions to the class or instructor.
MATH-505
3 Credits
This course explores Poisson processes and Markov chains with an emphasis on applications. Extensive use is made of conditional probability and conditional expectation. Further topics, such as renewal processes, Brownian motion, queuing models and reliability are discussed as time allows.
MATH-605
3 Credits
This course is an introduction to stochastic processes and their various applications. It covers the development of basic properties and applications of Poisson processes and Markov chains in discrete and continuous time. Extensive use is made of conditional probability and conditional expectation. Further topics such as renewal processes, reliability and Brownian motion may be discussed as time allows.
STAT-405
3 Credits
This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference.
STAT-406
3 Credits
This course is a continuation of STAT-405 covering classical and Bayesian methods in estimation theory, chi-square test, Neyman-Pearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference.

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