Note: You must establish a session for Fall Academic Term 2002 on wolverineaccess.umich.edu in order to use the link "Check Times, Location, and Availability". Once your session is established, the links will function.
This page was created at 8:01 PM on Thu, Oct 3, 2002.
STATS 100. Introduction to Statistical Reasoning.
Instructor(s):
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in SOC 210, STATS 265, 350, 400, 405, or 412, IOE 265, or ECON 404 or 405. (4). (MSA). (BS). (QR/1).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~bkg/stat100/
Provides an overview of the field of statistics, including methods of summarizing and analyzing data, statistical reasoning for learning from observations (experimental or sample), and techniques for dealing with uncertainties in drawing conclusions from collected data. Emphasis is on presenting underlying concepts rather than covering a variety of different methodologies. Course evaluation is based on a combination of a Thursday evening midterm examination, a final examination, and GSI input. The course format includes lectures and a discussion section (one hour per week).
STATS 265 / IOE 265. Probability and Statistics for Engineers.
Section 001.
Instructor(s):
Patrick Craig Hammett
Prerequisites & Distribution: MATH 116 and ENGR 101. No credit granted to those who have completed or are enrolled in STATS 311, 400, 405, or 412, or ECON 405. (4). (Excl). (BS). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Graphical Representation of Data; Axioms of Probability; Conditioning, Bayes Theorem; Discrete Distributions (Geometric, Binomial, Poisson); Continuous Distributions (Normal Exponential, Weibull), Point and Interval Estimation, Likelihood Functions, Test of Hypotheses for Means, Variances, and Proportions for One and Two Populations.
STATS 350(250/402). Introduction to Statistics and Data Analysis.
Instructor(s):
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in ECON 404 or 405, or IOE 265 or STATS 265, 400, 405, or 412. (4). (NS). (BS). (QR/1).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~bkg/stat350/
In this course students are introduced to the concepts and applications of statistical methods and data analysis. Statistics 350 has no prerequisite and has been elected by students whose mathematics background includes only high school algebra. Examples of applications are drawn from virtually all academic areas and some attention is given to statistical process control methods. The course format includes lectures (3 hours per week) and a laboratory (1.5 hours per week). The laboratory section deals with the computational aspects of the course and provides a forum for review of lecture material. For this purpose, students are introduced to the use of a statistical analysiscomputer package. Course evaluation is based on a combination of two examinations, a final examination, weekly homework, and lab participation.
STATS 400. Applied Statistical Methods.
Section 001.
Instructor(s):
Prerequisites & Distribution: High School Algebra. No credit granted to those who have completed or are enrolled in ECON 404 or 405, or STATS 250, 265, 350, 405, or 412. (4). (Excl). (BS). (QR/1).
Credits: (4).
Course Homepage: No homepage submitted.
Statistics and the scientific method; observational study versus designed experiment;
visualization; introduction to probability; statistical inference; confidence intervals; onesample tests of hypothesis; twosample problems; analysis of variance (ANOVA); blocked designs; tests for association and independence (chisquare tests); regression and correlation; and nonparametric tests. Course format includes lectures (3 hours per week) and a laboratory (1.5 hours per week).
STATS 401(403). Applied Statistical Methods II.
Section 001.
Instructor(s):
Kirsten T Namesnik
Prerequisites & Distribution: STATS 350 or 400. No credit granted to those who have completed or are enrolled in STAT 413. (4). (Excl). (BS).
Credits: (4).
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
STATS 405 / ECON 405. Introduction to Statistics.
Section 001.
Instructor(s):
Prerequisites & Distribution: MATH 116. Juniors and seniors may elect this course concurrently with ECON 101 or 102. No credit granted to those who have completed or are enrolled in IOE 265, STATS 265, 400 or 412. Students with credit for ECON 404 can only elect STATS 405 for 2 credits and must have permission of instructor. (4). (Excl). (BS). (QR/1).
Credits: (4).
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/econ/405/001.nsf
Principles of statistical inference, including: probability, experimental and theoretic derivation of sampling distributions, hypothesis testing, estimation, and simple regression.
STATS 406. Introduction to Statistical Computing.
Section 001.
Prerequisites & Distribution: One of STATS 350, 405, 412, or 425. (4). (Excl). (BS).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~gmichail/stat406F02/
Acquaints students with selected topics in statistical computing, including basic numerical aspects, iterative statistical methods, principles of graphical analyses, simulation and Monte Carlo methods, generation of random variables, stochastic modeling, importance sampling, and numerical and Monte Carlo integration. Three hours of lecture and one and onehalf hour laboratory session each week.
STATS 406. Introduction to Statistical Computing.
Section 002.
Instructor(s):
Prerequisites & Distribution: One of STATS 350, 405, 412, or 425. (4). (Excl). (BS).
Credits: (4).
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/stats/406/002.nsf
Acquaints students with selected topics in statistical computing, including basic numerical aspects, iterative statistical methods, principles of graphical analyses, simulation and Monte Carlo methods, generation of random variables, stochastic modeling, importance sampling, and numerical and Monte Carlo integration. Three hours of lecture and one and onehalf hour laboratory session each week.
STATS 412. Introduction to Probability and Statistics.
Section 001.
Prerequisites & Distribution: Prior or concurrent enrollment in MATH 215 and EECS 183. No credit granted to those who have completed or are enrolled in ECON 405, STATS 265, 400, or 405, or IOE 265. One credit granted to those who have completed or are enrolled in STATS 350. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~elevina/stat412/
The objectives of this course are to introduce students to the basic ideas of probability and statistical inference and to acquaint students with some important data analytic techniques, such as regression and the analysis of variance. Examples will emphasize applications to the natural sciences and engineering. There will be regular homework, two midterms, and a final exam.
STATS 425 / MATH 425. Introduction to Probability.
Instructor(s):
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No homepage submitted.
Basic concepts of probability; expectation, variance, covariance; distribution functions; and bivariate, marginal, and conditional distributions.
STATS 425 / MATH 425. Introduction to Probability.
Section 001.
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://www.math.lsa.umich.edu/~fomin/425.html
See Mathematics 425.001.
STATS 425 / MATH 425. Introduction to Probability.
Section 005.
Instructor(s):
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/math/425/005.nsf
See Mathematics 425.005.
STATS 426. Introduction to Theoretical Statistics.
Section 001.
Prerequisites & Distribution: STATS 425. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No homepage submitted.
This course covers the basic ideas of statistical inference, including sampling distributions, estimation, confidence intervals, hypothesis testing, regression, analysis of variance, nonparametric testing, and Bayesian inference. The sequence of Statistics 425/426 serves as a prerequisite for more advanced Statistics courses. Regular homework and a final exam.
Topic covered include:
 Random Variables
 Joint Distributions
 Induced Distributions
 Expectation
 The Law of Large Numbers
 The Central Limit Theorem
 Simulation
 Populations and Samples
 The Chisquared, t, and F Distributions
 Estimation: The Method of Moments
 Maximum Likelihood Estimation
 More on Maximum Likelihood Estimation
 Bias, Variance, and MSE
 The Cramer Rao Inequality
 Exponential Families and Sufficiency
 Confidence Intervals
 Approximate Confidence Intervals
 The Bootstrap
 Asymptotics of the MLE
 Tests and Confidence Intervals
 Neyman Pearson
 Likelihood Ratio Tests
 ChiSquared Tests
 Goodness of Fit Tests
 The Sample Distribution Function
 Decision Analysis
 Bayesian Inference
 The Two Sample Problem
 More on the Two Sample Problem
 Rank Tests
 One Way ANOVA
 Simultaneous Confidence
 Two Way ANOVA
 Categorical Data
 Simple Linear Regression
 Multiple Regression
STATS 430. Applied Probability.
Section 001.
Instructor(s):
Prerequisites & Distribution: STATS 425. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No homepage submitted.
Review of probability theory; introduction to random walks; counting and Poisson processes; Markov chains in discrete and continuous time; equations for stationary distributions; introduction to Brownian motion. Selected applications such as branching processes, financial modeling, genetic models, the inspection paradox, inventory and queuing problems, prediction, and/or risk analysis. Selected optional topics such as hidden Markov chains, martingales, renewal theory, and/or stationary process.
STATS 466 / IOE 466 / MFG 466. Statistical Quality Control.
Instructor(s):
Jianjun Shi
Prerequisites & Distribution: STATS 265 and 401 or IOE 366. (4). (Excl). (BS). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Design and analysis of procedures for forecasting and control of production processes. Topics include: attribute and variables sampling plans; sequential sampling plans; rectifying control procedures; and charting, smoothing, forecasting, and prediction of discrete time series.
STATS 466 / IOE 466 / MFG 466. Statistical Quality Control.
Section 001.
Instructor(s):
Yong Chen
Prerequisites & Distribution: STATS 265 and 401 or IOE 366. (4). (Excl). (BS). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/ioe/466/001.nsf
Quality Improvement Philosophies; Modeling Process Quality, Statistical Process Control, Control Charts for Variables and Attributes, CUSUM and EWMA, Short Production Runs, Multivariate Quality Control, Auto Correlation, Engineering Process Control, Economic Design of Charts, Fill Control, Precontrol, Adaptive Schemes, Process Capability, Specifi cations and Tolerances, Gage Capability Studies, Acceptance Sampling by Attributes and Variables, International Quality Standards.
STATS 470. Introduction to the Design of Experiments.
Section 001.
Prerequisites & Distribution: STATS 350. (4). (Excl). (BS).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~dbingham/Stat470/index.html
This course will introduce students to basic principles in classical experimental design, including randomization, replication, confounding, interaction, covariates, and use of the general linear model. Students will be introduced to the following designs: completely randomized, randomized blocks, Latin squares, incomplete blocks, factorial, split plot, Taguchi, response surface, and optimal. There will be regular assignments and a final exam. Class format is 3 hours of lecture and 1.5 hours of laboratory per week.
STATS 499. Honors Seminar.
Instructor(s):
Prerequisites & Distribution: Permission of departmental Honors advisor. (23). (Excl). (INDEPENDENT).
Credits: (23).
Course Homepage: No homepage submitted.
Advanced topics, reading and/or research in applied or theoretical statistics.
STATS 500. Applied Statistics I.
Prerequisites & Distribution: MATH 417, and STATS 350 or 426. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~faraway/stat500/
Linear Models: Definition, fitting, inference, interpretation of
results, meaning of regression coefficients, identifiablity, lack of
fit, multicollinearity, ridge regression, principal components
regression, partial least squares, regression splines, GaussMarkov
theorem, variable selection, diagnostics, transformations, influential
observations, robust procedures, ANOVA and analysis of covariance,
Randomised block, and factorial designs.
Computing:
The software I will be using for the course is R. R is very similar
to S+, the software I have used for this course in the past. R is
free with Windows and Unix versions. You can download your own copy
and use it wherever you find convenient.
STATS 503. Applied Multivariate Analysis.
Section 001.
Prerequisites & Distribution: STATS 500. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~gmichail/stat503F02/
Topics in applied multivariate analysis including Hotelling's T^{2} multivariate ANOVA, discriminant functions, factor analysis, principal components, canonical correlations, and cluster analysis. Selected topics from: maximum likelihood and Bayesian methods, robust estimation and survey sampling. Applications and data analysis using a computer will be stressed.
STATS 504. Statistical Consulting.
Section 001.
Prerequisites & Distribution: STATS 401 or 500. (3). (Excl). (BS). May be elected for a total of nine credits.
Credits: (3).
Course Homepage: No homepage submitted.
Applications of statistics to problems in engineering, physical sciences, and social sciences; students will be expected to analyze data and write reports.
STATS 505 / ECON 671. Econometric Analysis I.
Section 001.
Instructor(s):
Prerequisites & Distribution: Permission of instructor. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/econ/671/001.nsf
No Description Provided. Contact the Department.
STATS 525 / MATH 525. Probability Theory.
Section 001.
Instructor(s):
Charles R Doering
Prerequisites & Distribution: MATH 450 or 451. Students with credit for STATS 425/MATH 425 can elect STATS 525/MATH 525 for only one credit. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No homepage submitted.
See Mathematics 525.001.
STATS 575 / ECON 678. Econometric Theory I.
Section 001.
Prerequisites & Distribution: MATH 417 and 425, or ECON 671, 672, and 600. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://coursetools.ummu.umich.edu/2002/fall/econ/678/001.nsf
The purpose of this course is to develop the results of asymptotic distribution theory needed for statistical inference in econometrics and to use these results to derive the properties of various estimators and test procedures used in econometrics. The course is a prerequisite for Statistics 576 (Econometric Theory II).
This page was created at 8:01 PM on Thu, Oct 3, 2002.
University of Michigan  College of LS&A  Student Academic Affairs  LS&A Bulletin Index  Department Homepage
This page maintained by LS&A Academic Information and Publications, 1228 Angell Hall
Copyright © 2002 The Regents of the University of Michigan,
Ann Arbor, MI 48109 USA +1 734 7641817
Trademarks of the University of Michigan may not be electronically or otherwise altered or separated from this document or used for any nonUniversity purpose.
