Linlin Chen
Associate Professor
School of Mathematical Sciences
College of Science
585-475-7619
Office Hours
Tuesday 4-5pm and by Appointment.
Office Location
Linlin Chen
Associate Professor
School of Mathematical Sciences
College of Science
Education
BS, Peking University (China); Master of Computer Science, Rice University; MA, Ph.D., University of Rochester
585-475-7619
Select Scholarship
Journal Paper
Chen, Linlin, et al. "Transcriptome Signature in Young Children with Acute Otitis Media due to Streptococcus Pneumoniae." Microbes and Infection 14. (2012): 600-609. Print.
Linlin, Chen, et al. "Hypertonic Saline and Desmopressin: A Simple Strategy for Safe Correction of Severe Hyponatremia." American Journal of Kidney Disease. (2012): doi:10.1053/j.ajkd.2012.11.032. Web.
Published Conference Proceedings
Chen, Linlin, et al. "Sentinel Lymph Node: A Tale of Two Methods, A Natural Experiment." Proceedings of the Annual Meeting of the American Roentgen Ray Society (ARRS). Ed. American Roentgen Ray Society. Vancouver, BC: n.p., 2012. Print.
Formal Presentation
Chen, Linlin. “Overcoming Adverse Effects of Correlationsin Microarray Data Analysis.” 2010 Joint Statistical Meetings. Vancouver, Canada.August, 2010. Presentation.
Currently Teaching
STAT-325
Design of Experiments
3 Credits
This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include single-factor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits.
STAT-406
Mathematical Statistics II
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.
STAT-511
Statistical Software - R
3 Credits
This course is an introduction to the statistical-software package R, which is often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions; graphics; matrices and arrays; simulations and app development with Shiny.
STAT-584
Categorical Data Analysis
3 Credits
This course is intended to introduce students to categorical data analysis. Topics include: contingency tables, matched pair analysis, Fisher's exact test, logistic regression, analysis of odds ratios, log linear models, multi-categorical logit models, ordinal and paired response analysis.
STAT-611
Statistical Software - R
3 Credits
This course is an introduction to the statistical-software package R, which is often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions; graphics; matrices and arrays; simulations and app development with Shiny.
STAT-641
Applied Linear Models - Regression
3 Credits
A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building.
STAT-784
Categorical Data Analysis
3 Credits
The course develops statistical methods for modeling and analysis of data for which the response variable is categorical. Topics include: contingency tables, matched pair analysis, Fisher's exact test, logistic regression, analysis of odds ratios, log linear models, multi-categorical logit models, ordinal and paired response analysis.
In the News
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November 15, 2021
Engineering faculty awarded NSF funding to improve computing system memory
Dorin Patru and Linlin Chen, faculty-researchers at RIT, received a grant from the National Science Foundation to upgrade functions of programmable memory. They, along with colleagues from University of Rochester, will develop new algorithms to improve the internal computing memory system to enable scalable and more robust performance.