Annual 2018-2019 Class Schedule: Department of Statistics and Data Science

Annual 2018-2019 Class Schedule

This schedule lists the courses the Department of Statistics intends to offer in 2018-2019. Please contact us with questions or concerns at stats@northwestern.edu or 847-491-3974.

Course #	Course Title	Fall	Winter	Spring
UNDERGRADUATE COURSES
202	Introduction to Statistics		Kuyper MWF 9:00-9:50am	Kuyper MWF 9:00-9:50am
202 Introduction to Statistics Data collection, summarization, correlation, regression, probability, sampling, estimation, tests of significance. Does not require calculus and makes minimal use of mathematics. May not receive credit for both STAT 202-0 and STAT 210-0.
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
202-0-20	Introduction to Statistics	Kuyper MWF 9:00-9:50am
202-0-20 Introduction to Statistics Data collection, summarization, correlation, regression, probability, sampling, estimation, tests of significance. Does not require calculus and makes minimal use of mathematics. May not receive credit for both STAT 202-0 and STAT 210-0.
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
202-0-21	Introduction to Statistics	Tipton MWF 1:00-1:50pm
202-0-21 Introduction to Statistics Data collection, summarization, correlation, regression, probability, sampling, estimation, tests of significance. Does not require calculus and makes minimal use of mathematics. May not receive credit for both STAT 202-0 and STAT 210-0.
Tipton Elizabeth Tipton Associate Professor of Statistics Research interests include: social statistics, education statistics, randomized experiments, meta-analysis.
210	Introductory Statistics for the Social Sciences	Lewis MWF 11:00-11:50am Disc: T 5pm or Th 4pm	Lewis MWF 12:00-12:50pm Disc: T 5pm or Th 4pm	Kutzman MWF 2:00-2:50pm Disc: T 5pm or Th 4pm
210 Introductory Statistics for the Social Sciences A mathematical introduction to probability theory and statistical methods, including properties of probability distributions, sampling distributions, estimation, confidence intervals, and hypothesis testing. STAT 210-0 is primarily intended for economics majors. May not receive credit for both STAT 202-0 and STAT 210-0. Prerequisite: strong background in high school algebra (calculus is not required).
Bio coming soon
Bio coming soon
Bio coming soon
232	Applied Statistics		Tanner TTh 12:30-1:50pm
232 Applied Statistics Basic concepts of using statistical models to draw conclusions from experimental and survey data. Topics include simple linear regression, multiple regression, analysis of variance, and analysis of covariance. Practical application of the methods and the interpretation of the results will be emphasized. Prerequisites: STAT 202-0, STAT 210-0, or equivalent; MATH 220-0.
Martin Tanner Professor of Statistics Research interests include: Markov chain Monte Carlo methods for Bayesian and frequentist inference, nonparametric estimation of the hazard function for right-censored and interval-censored data, methodology for ecological Inference, applications of multiple imputation to censored regression data, as well as models and measures of interrater agreement/disagreement.
320-3	Statistical Theory and Methods 3			Samia TTh 9:30-10:50pm
320-3 Statistical Theory and Methods 3 Comparison of parameters, goodness-of-fit tests, regression analysis, analysis of variance, and nonparametric methods. Prerequisites: STAT 320-2, MATH 240-0.
Noelle Samia Associate Professor of Statistics Research interests include: time-series analysis, nonlinear time-series modeling with emphasis to threshold models, statistical inference for infectious diseases and epidemiology, statistical ecology, statistical applications to biomedical research.
				Samia TTh 12:30-1:50pm
320-3 Statistical Theory and Methods 3 Comparison of parameters, goodness-of-fit tests, regression analysis, analysis of variance, and nonparametric methods. Prerequisites: STAT 320-2, MATH 240-0.
Noelle Samia Associate Professor of Statistics Research interests include: time-series analysis, nonlinear time-series modeling with emphasis to threshold models, statistical inference for infectious diseases and epidemiology, statistical ecology, statistical applications to biomedical research.
332	Statistics for Life Sciences			H. Jiang TTh 11:00-12:20pm
332 Statistics for Life Sciences Application of statistical methods and data analysis techniques to the life sciences. Parametric statistics, nonparametric approaches, resampling-based approaches. Prerequisite: 1 introductory statistics course. *NOTE: This course does not count toward a statistics major or minor
Hongmei Jiang Associate Professor of Statistics Jiang focuses on developing statistical and computational methodologies to analyze and understand the massive amount of data generated by high throughput biological technologies, especially microarray and next generation sequencing based genomics, methylation, and metagenomics data analysis.
370	Human Rights Statistics	Spencer TTh 3:30-4:50pm
370 Human Rights Statistics Development, analysis, interpretation, use, and misuse of statistical data and methods for description, evaluation, and political action regarding war, disappearances, justice, violence against women, trafficking, profiling, elections, hunger, refugees, discrimination, etc. Prerequisites: Two of STAT 325-0, STAT 350-0, STAT 320-2,STAT 302-3; or ECON 381-1, ECON 381-2; or MMSS 386-1, MMSS 386-2; or IEMS 303-0, IEMS 304-0.
Bruce Spencer Professor of Statistics Spencer works in the interface of statistics and public policy with a special focus on the design and evaluation of large-scale statistical data programs. He is currently conducting a cost-benefit analysis to see how much accuracy is needed for the next census (in 2020), and at what cost. With Prof. Seth Stein (Earth & Planetary Sciences), he is jointly studying accuracy of seismic hazard forecasts. Spencer has developed statistical methods for assessing the accuracy of verdicts in criminal cases when the truth is unknown.
383	Probability and Statistics for ISP		Severini MWF 1:00-1:50pm Disc: T 1:00-1:50pm
383 Probability and Statistics for ISP Probability and statistics. Ordinarily taken only by students in ISP; permission required otherwise. May not receive credit for both STAT 383-0 and any of STAT 320-1; MATH 310-1, MATH 311-1, MATH 314-0, MATH 385-0; EECS 302-0; or IEMS 202-0. Prerequisites: MATH 281-1,MATH 281-2, MATH 281-3; PHYSICS 125-1, PHYSICS 125-2, PHYSICS 125-3. *NOTE: This course does not count toward a statistics major or minor
Thomas Severini Professor of Statistics Research interests include: likelihood-based statistical methods such as maximum likelihood estimation and tests and confidence regions based on the likelihood ratio statistic, the application of statistical methods to the analysis of sports data.
398	Undergraduate Seminar			Severini MW 2:00-3:20pm
398 Undergraduate Seminar No description available.
Thomas Severini Professor of Statistics Research interests include: likelihood-based statistical methods such as maximum likelihood estimation and tests and confidence regions based on the likelihood ratio statistic, the application of statistical methods to the analysis of sports data.
COURSES OPEN TO UNDERGRADUATE AND GRADUATE STUDENTS
301-1	Data Science 1	Kuyper MW 4:00-5:20pm
301-1 Data Science 1 Data Science 1 focuses on data management, manipulation, and visualization skills and techniques for exploratory data analysis. Prerequisite: STAT 202-0 or equivalent
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
301-2	Data Science 2		Kuyper MW 4:00-5:20pm
301-2 Data Science 2 Data Science 2 focuses on foundational analytic methods such as linear regression, resampling, and tree-based methods. Prerequisite: STAT 301-1 or consent of instructor.
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
301-3	Data Science 3			Schauer MW 4:00-5:20pm
301-3 Data Science 3 Data Science 3 focuses on methods such as support vector machines, clustering, and neural networks. Prerequisite: STAT 301-2 or consent of instructor.
Schauer https://sites.northwestern.edu/jmschauer/
302	Data Visualization			Kuyper TTH 9:30-10:50am
302 Data Visualization Introduction to the knowledge, skills, and tools required to visualize data of various formats across statistical domains and to create quality visualizations for both data exploration and presentation. Prerequisite: STAT 202-0 or equivalent.
Arend Kuyper Assistant Professor of Instruction Kuyper’s work is dedicated to the development and implementation of methods, techniques, and strategies for teaching statistics. His current focus is on incorporating data science methods and topics into the introductory statistics course and developing data science courses with a focus on application.
320-1	Statistical Theory and Methods 1	Andrews MWF 12:00-12:50pm
320-1 Statistical Theory and Methods 1 Sample spaces, computing probabilities, random variables, distribution functions, expected values, variance, correlation, limit theory. May not receive credit for both STAT 320-1 and any of STAT 383-0, MATH 310-1, MATH 311-1, MATH 314-0, MATH 385-0, EECS 302-0, or IEMS 202-0. Corequisites: STAT 202-0 or STAT 210-0, MATH 234-0.
Beth Andrews Associate Professor of Statistics Research interests include: time series analysis, spatial statistics, stochastic processes and their applications, robust statistics, extreme value theory, and financial mathematics. The focus of her recent research is model fitting and prediction for nonlinear, non-Gaussian processes observed over space and time. This work has applications in the areas of economics and finance, the geosciences, and signal processing.
		Andrews MWF 2:00-2:50pm
320-1 Statistical Theory and Methods 1 Sample spaces, computing probabilities, random variables, distribution functions, expected values, variance, correlation, limit theory. May not receive credit for both STAT 320-1 and any of STAT 383-0, MATH 310-1, MATH 311-1, MATH 314-0, MATH 385-0, EECS 302-0, or IEMS 202-0. Corequisites: STAT 202-0 or STAT 210-0, MATH 234-0.
Beth Andrews Associate Professor of Statistics Research interests include: time series analysis, spatial statistics, stochastic processes and their applications, robust statistics, extreme value theory, and financial mathematics. The focus of her recent research is model fitting and prediction for nonlinear, non-Gaussian processes observed over space and time. This work has applications in the areas of economics and finance, the geosciences, and signal processing.
320-2	Statistical Theory and Methods 2		W. Jiang TTh 11:00-12:20pm
320-2 Statistical Theory and Methods 2 Sampling, parameter estimation, confidence intervals, hypothesis tests. Prerequisite: STAT 320-1 or MATH 310-1.
Wenxin Jiang Professor of Statistics Research interests include: statistical theory, data sciences, biostatistics, econometrics, and applications in social sciences. He has published papers on performance measurements in data mining, Bayesian statistics based on assumptions of moments, model selection and combination, and partial identification.
			Andrews MWF 2:00-2:50pm
320-2 Statistical Theory and Methods 2 Sampling, parameter estimation, confidence intervals, hypothesis tests. Prerequisite: STAT 320-1 or MATH 310-1.
Beth Andrews Associate Professor of Statistics Research interests include: time series analysis, spatial statistics, stochastic processes and their applications, robust statistics, extreme value theory, and financial mathematics. The focus of her recent research is model fitting and prediction for nonlinear, non-Gaussian processes observed over space and time. This work has applications in the areas of economics and finance, the geosciences, and signal processing.
325	Survey Sampling	Spencer TTh 9:30-10:50am
325 Survey Sampling Probability sampling, simple random sampling, error estimation, sample size, stratification, systematic sampling, replication methods, ratio and regression estimation, cluster sampling. Prerequisites: MATH 230 and 2 quarters of statistics, or consent of instructor.
Bruce Spencer Professor of Statistics Spencer works in the interface of statistics and public policy with a special focus on the design and evaluation of large-scale statistical data programs. He is currently conducting a cost-benefit analysis to see how much accuracy is needed for the next census (in 2020), and at what cost. With Prof. Seth Stein (Earth & Planetary Sciences), he is jointly studying accuracy of seismic hazard forecasts. Spencer has developed statistical methods for assessing the accuracy of verdicts in criminal cases when the truth is unknown.
344	Statistical Computing	Wang TTh 12:30-1:50pm
344 Statistical Computing Exploration of theory and practice of computational statistics with emphasis on statistical programming in R. Prerequisite: STAT 320-2 or equivalent.
Ji-Ping Wang Professor of Statistics, Adjunct Professor of Molecular BioSciences Research interests include: statistical applications in bioinformatics and computational biology
348	Applied Multivariate Analysis	Severini TTh 11:00-12:20pm
348 Applied Multivariate Analysis Statistical methods for describing and analyzing multivariate data. Principal component analysis, factor analysis, canonical correlation, clustering. Emphasis on statistical and geometric motivation, practical application, and interpretation of results. Prerequisites: STAT 320-2, MATH 240-0.
Thomas Severini Professor of Statistics Research interests include: likelihood-based statistical methods such as maximum likelihood estimation and tests and confidence regions based on the likelihood ratio statistic, the application of statistical methods to the analysis of sports data.
350	Regression Analysis		H. Jiang TTh 12:30-1:50pm
350 Regression Analysis Simple linear regression and correlation, multiple regression, residual analysis, selection of subsets of variables, multi-collinearity and shrinkage estimation, nonlinear regression. Prerequisite or corequisite: STAT 320-2
Hongmei Jiang Associate Professor of Statistics Jiang focuses on developing statistical and computational methodologies to analyze and understand the massive amount of data generated by high throughput biological technologies, especially microarray and next generation sequencing based genomics, methylation, and metagenomics data analysis.
			H. Jiang TTh 2:00-3:20pm
350 Regression Analysis Simple linear regression and correlation, multiple regression, residual analysis, selection of subsets of variables, multi-collinearity and shrinkage estimation, nonlinear regression. Prerequisite or corequisite: STAT 320-2
Hongmei Jiang Associate Professor of Statistics Jiang focuses on developing statistical and computational methodologies to analyze and understand the massive amount of data generated by high throughput biological technologies, especially microarray and next generation sequencing based genomics, methylation, and metagenomics data analysis.
351	Design and Analysis of Experiments			H. Jiang TTh 2:00-3:20pm
351 Design and Analysis of Experiments Methods of designing experiments and analyzing data obtained from them: one-way and two-way layouts, incomplete block designs, factorial designs, random effects, split-plot and nested designs. Prerequisite: STAT 320-1 or equivalent.
Hongmei Jiang Associate Professor of Statistics Jiang focuses on developing statistical and computational methodologies to analyze and understand the massive amount of data generated by high throughput biological technologies, especially microarray and next generation sequencing based genomics, methylation, and metagenomics data analysis.
356	Hierarchical Linear Models			Hedges T 3:00-5:30pm
356 Hierarchical Linear Models Introduction to the theory and application of hierarchical linear models. Two and three level linear models, hierarchical generalized linear models, and application of hierarchical models to organizational research and growth models. Prerequisites: STAT 320-2, STAT 350-0.
Larry Hedges Board of Trustees Professor of Statistics Research interests include: development and application of statistical methods for the social, medical, and biological sciences.
359	Topics in Statistics	Tanner TTh 9:30-10:50am	Tanner TTh 9:30-10:50am	W. Jiang TTh 12:30-1:50pm
359 Topics in Statistics Topics in theoretical and applied statistics, to be chosen by the instructor. This course may be taken more than once for credit. Prerequisite: consent of instructor.
Martin Tanner Professor of Statistics Research interests include: Markov chain Monte Carlo methods for Bayesian and frequentist inference, nonparametric estimation of the hazard function for right-censored and interval-censored data, methodology for ecological Inference, applications of multiple imputation to censored regression data, as well as models and measures of interrater agreement/disagreement.
Martin Tanner Professor of Statistics Research interests include: Markov chain Monte Carlo methods for Bayesian and frequentist inference, nonparametric estimation of the hazard function for right-censored and interval-censored data, methodology for ecological Inference, applications of multiple imputation to censored regression data, as well as models and measures of interrater agreement/disagreement.
Wenxin Jiang Professor of Statistics Research interests include: statistical theory, data sciences, biostatistics, econometrics, and applications in social sciences. He has published papers on performance measurements in data mining, Bayesian statistics based on assumptions of moments, model selection and combination, and partial identification.
365	Introduction to Financial Statistics		Severini MWF 11:00-11:50am
365 Introduction to Financial Statistics Statistical methods for analyzing financial data. Models for asset returns, portfolio theory, parameter estimation. Prerequisites: STAT 320-3, MATH 240-0.
Thomas Severini Professor of Statistics Research interests include: likelihood-based statistical methods such as maximum likelihood estimation and tests and confidence regions based on the likelihood ratio statistic, the application of statistical methods to the analysis of sports data.
GRADUATE COURSES
330-1	Applied Statistics for Research 1	Tanner MF 9:30-10:50am Disc: W 9:00-9:50am
330-1 Applied Statistics for Research 1 First Quarter: Design of experiments and surveys, numerical summaries of data, graphical summaries of data, correlation and regression, probability, sample mean, sample proportion, confidence intervals and tests of significance, one and two sample problems, ANOVA. Second Quarter: Simple linear regression, inference, diagnostics, multiple regression diagnostics, autocorrelation, 1-way ANOVA, power and sample size determination, 2-way ANOVA, ANCOVA, randomized block designs.
Martin Tanner Professor of Statistics Research interests include: Markov chain Monte Carlo methods for Bayesian and frequentist inference, nonparametric estimation of the hazard function for right-censored and interval-censored data, methodology for ecological Inference, applications of multiple imputation to censored regression data, as well as models and measures of interrater agreement/disagreement.
420-1	Intr to Statistical Theory & Methodology 1	Samia TTh 11:00-12:20pm
420-1 Intr to Statistical Theory & Methodology 1 Distribution theory, characteristic functions, moments and cumulants, random variables, sampling theory, and common statistical distributions.
Noelle Samia Associate Professor of Statistics Research interests include: time-series analysis, nonlinear time-series modeling with emphasis to threshold models, statistical inference for infectious diseases and epidemiology, statistical ecology, statistical applications to biomedical research.
420-2	Stat Theory/Meth 2		Wang TTh 11:00-12:20pm
420-2 Stat Theory/Meth 2 Methods of estimation, hypothesis tests, confidence intervals, least squares, likelihood methods, and large-sample methods.
Ji-Ping Wang Professor of Statistics, Adjunct Professor of Molecular BioSciences Research interests include: statistical applications in bioinformatics and computational biology
420-3	Intr to Statistical Theory & Methodology 3			W. Jiang TTh 11:00-12:20pm
420-3 Intr to Statistical Theory & Methodology 3 Theories of inference, multivariate methods, and contingency tables.
Wenxin Jiang Professor of Statistics Research interests include: statistical theory, data sciences, biostatistics, econometrics, and applications in social sciences. He has published papers on performance measurements in data mining, Bayesian statistics based on assumptions of moments, model selection and combination, and partial identification.
456	Generalized Linear Models	Samia TTh 2:00-3:20pm
456 Generalized Linear Models Inference and fitting of generalized linear models with application to classical linear models, binomial and multinomial logit models, log-linear models, Cox's proportional hazards model and GEE's for longitudinal data. Prerequisites: STAT 350-0 and STAT 420-3
Noelle Samia Associate Professor of Statistics Research interests include: time-series analysis, nonlinear time-series modeling with emphasis to threshold models, statistical inference for infectious diseases and epidemiology, statistical ecology, statistical applications to biomedical research.
461	Advanced Topics in Statistics	Spencer MW 9:30-10:50am	W. Jiang TTh 12:30-1:50pm	Wang TTh 9:30-10:50am
461 Advanced Topics in Statistics No description available.
Bruce Spencer Professor of Statistics Spencer works in the interface of statistics and public policy with a special focus on the design and evaluation of large-scale statistical data programs. He is currently conducting a cost-benefit analysis to see how much accuracy is needed for the next census (in 2020), and at what cost. With Prof. Seth Stein (Earth & Planetary Sciences), he is jointly studying accuracy of seismic hazard forecasts. Spencer has developed statistical methods for assessing the accuracy of verdicts in criminal cases when the truth is unknown.
Wenxin Jiang Professor of Statistics Research interests include: statistical theory, data sciences, biostatistics, econometrics, and applications in social sciences. He has published papers on performance measurements in data mining, Bayesian statistics based on assumptions of moments, model selection and combination, and partial identification.
Ji-Ping Wang Professor of Statistics, Adjunct Professor of Molecular BioSciences Research interests include: statistical applications in bioinformatics and computational biology
465	Statistical Methods for Bioinformatics and Computational Biology		Wang TTh 9:30-10:50am
465 Statistical Methods for Bioinformatics and Computational Biology An introduction of statistical methodologies in cutting-edge fields of computational biology and bioinformatics topics including microarray gene expression data analysis; biological sequence analysis; EST and SAGE data analysis.
Ji-Ping Wang Professor of Statistics, Adjunct Professor of Molecular BioSciences Research interests include: statistical applications in bioinformatics and computational biology

Annual 2018-2019 Class Schedule

UNDERGRADUATE COURSES

COURSES OPEN TO UNDERGRADUATE AND GRADUATE STUDENTS

GRADUATE COURSES