stats 600 umich

Other possible topics include semi-parametric models and efficiency issues. Pre-requisites: MATH 451, STATS 425, and STATS 426 or equivalent courses in probability, statistics and real analysis. Advisory Pre-requisite: Students should have a strong preparation in either biology or some branch of quantitative analysis (mathematics, statistics, or computer science), but not necessarily in both domains. Students will be expected to complete a course project and present to group. Statistics 506: Computational Methods and Tools in Statistics, Selected topics in computational statistics including: managing and processing large data sets, parallel and distributed programming, simulation and Monte Carlo methods, interactive statistical methods, and optimization. PSYCH 613, ECON 405) and graduate or advanced undergraduate standing, or permission of instructor. Topics vary by instructor.

X���C ��A1C(?��%��l�>1�1�`~�o �`�iS=�!� Statistics 701: Special Topics in Applied Statistics II.

Pre-requisites: MATH 451 or equivalent knowledge of real analysis. It also covers issues related to data collection, study design, and interpretation of findings, including missing data, non-representative samples, causality, and designed experiments. Pre-requisites: STATS 570 or permission of instructor. (3 Credits), Pre-requisites: STATS 520 or equivalent course in measure theory and STATS 611, Statistics 617: Advanced Topics in Quantitative Methodology, This course explores and critiques advanced methods for conducting quantitative research in the social sciences.

Learn more. Pre-requisites: Graduate level courses in Statistics at the level of 500 and 501 or permission of instructor. The modeling activities include problems arising in the science, engineering and the humanities and will include both quantitative and qualitative features. Prerequisites: STATS 510 or equivalent, real analysis (Math 451 or equivalent). Statistics 700: Special Topics in Applied Statistics I. Pre-requisite: STATS 501 and graduate standing. Statistics 600: Regression Analysis.

(3 Credits). (3-4 Credits). (3 Credits). The topics covered will include univariate and multivariate families of distributions, likelihood principle, point estimation, confidence regions, hypothesis tests, large sample properties, and other selected topics in contemporary methods. Statistics 600: Applied statistics and data analysis I. Instructors. Topics covered include Markov chains in discrete and continuous time, Poisson processes, Brownian motion, random walks, and their applications in key scientific and engineering areas. Graduate standing.

(3 Credits).

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