Linlin Chen Headshot

Linlin Chen

Associate Professor

School of Mathematical Sciences
College of Science

585-475-7619
Office Hours
TR: 10:45-12
Office Location

Linlin Chen

Associate Professor

School of Mathematical Sciences
College of Science

Education

BS, Beijing University (China); MCS, Rice University; MA, Ph.D., University of Rochester

Bio

<p>&nbsp;</p>

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-641
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-325
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-584
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-784
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.