Full Course List
201 Statistics and Public Policy
Basic statistical concepts and techniques introduced via case studies of interesting public policy issues. The cases illustrate methods of data collection and analysis.
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.
210 Introductory Statistics for the Social Sciences
Introduction to basic concepts and methods of statistics and probability. Methods of data collection, descriptive statistics, probability, estimation, sampling distributions, confidence intervals, hypothesis testing. Contact the Economics department via email econ@northwestern.edu or phone 847-491-5140 regarding this class, including obtaining permission numbers, all TA information, etc.
232 Applied Statistics
Basic concepts of using statistical models to draw conclusions from experimental and survey data. Topics to be covered include simple linear regression, multiple regression, analysis of variance, and analysis of covariance. Practical application of the methodology and the interpretation of the results will be emphasized. Examples will be drawn from a wide range of fields. Prerequisites: 202, 210, or equivalent; MATH 220.
320-1,2 Statistical Theory and Methods
1. Distribution functions, densities, measurement of location and scale, random sampling, random variables, sampling statistics, hypothesis tests, confidence intervals, parameter estimation, and nonparametric methods. 2. Correlation and regression, contingency tables, analysis of variances, design and analysis of experiments. Prerequisites: MATH 234 and 240.
325 Survey Sampling
Probability sampling, simple random sampling, error estimation, determination of sample size, stratification, systematic sampling, replication and pseudo- replication methods, ratio and regression estimation, cluster sampling, multiphase sampling, and nonsampling errors.
338 History of Statistics
Historical survey of the development of modern statistics, from Bernoulli’s law of large numbers to the contributions of R.A. Fisher. Prerequisite: IEMS 304 or equivalent
344 Statistical Computing
Exploration of the theoretical and practical problems in the development and use of statistical computing systems for numerical and graphical analysis of data. Prerequisite: Permission of the instructor.
345 Statistical Demography
Self contained introduction to statistical theory of demographic rates (births, deaths, migration) in multi-state setting; statistical model underlying formal demography; analysis of error in demographic forecasting. Prerequisite: MATH 217; STAT 320 or equivalent
350 Regression Analysis
Development of statistical techniques for linear regression, with an emphasis on applications to empirical data. Least-squares methods, confidence intervals, tests of hypotheses, measurement of association, and residual analysis. Criteria and methods of model selection. Computational and inferential procedures for nonlinear regression. Use of computer packages is emphasized throughout the course.
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, Latin squares, Youden squares, factorial and fractional factorial designs, random-effects and mixed-effects models, and split-plot and nested designs.
352 Nonparametric Statistical Methods
A survey of nonparametric methods with emphasis on their theoretical rationale, basic properties, and typical applications. Topics include the sign, Mann-Whitney, Wilcoxon signed rank, rank correlation, Kruskal-Wallis, and Friedman tests.
355 Analysis of Qualitative Data
An introduction to the analysis of qualitative data with emphasis on the use of log-linear models. Topics include polytomous responses, two-way tables, multiway tables, logits, multinomial responses, incomplete tables, symmetric tables, adjustment techniques, and latent-class models.
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. Recent topics courses include Statistical Methods in Epidemiology, Statistical Computing, and Applied Multivariate Analysis.
The following courses were recently taught as Statistics 359.
Statistical Methods in DNA Identification (Zabell)
Applied Time Series Modeling and Forecasting (Andrews)Topics in Statistical Data Mining (W Jiang)
Mixture models and application (Wang)Simultaneous Statistical Inference (H Jiang)
Causal Inferences (Hedges)
STAT 365 Introduction to Financial Statistics
STAT 398 Undergraduate Seminar
STAT 399 Independent Study
