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STATS 100. Introduction to Statistical Reasoning.
THERE WILL BE ONE MIDTERM EXAM ON THURS,FEB 21, 6:007:30 P.M. FOR STATS 100.
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). May not be repeated for credit.
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 170. The Art of Scientific Investigation.
Section 001 – THERE WILL BE THREE MONDAY EVENING MIDTERM EXAMS FOR STATISTICS 170. Meets with Statistics 408.001.
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in STATS 408. (4). (MSA). (BS). (QR/1). May not be repeated for credit.
Credits: (4).
Course Homepage: http://coursetools.ummu.umich.edu/2003/winter/stats/408/001.nsf
This course will explore the critical thought processes involved in a scientific investigation. Concepts covered will include: the role of empiricism, modeling, the nature of variability, the design of scientific experiments (advantages and disadvantages), the role of randomization, the measurement process, possible biases, the use of controls, and the evaluation of final results. Examples from the history of science will be used to illustrate successes and failures in science and various ethical issues will be considered. The course format includes three lectures and a laboratory (1.5 hours per week).
TEXTBOOKS:
The Fifth Discipline, Peter M. Senge,
Doubleday Currency, and
The New Economics for Industry Government Education,
W. Edwards Deming,
2nd Edition,
MIT.
STATS 265 / IOE 265. Probability and Statistics for Engineers.
Section 001.
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. May not be repeated for credit.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://wwwpersonal.engin.umich.edu/~goovaert/cours4.html
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.
THERE WILL BE TWO MIDTERM EXAMS ON THURS, FEB 14 AND MAR 21, 6:007:30 PM.
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). May not be repeated for credit.
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. STATS 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):
Elizaveta Levina
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). May not be repeated for credit.
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~elevina/stat400/index.html
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.
Prerequisites & Distribution: STATS 350 or 400. No credit granted to those who have completed or are enrolled in STAT 413. (4). (Excl). (BS). May not be repeated for credit.
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~kshedden/Courses/Stat401/index.html
An intermediate course in applied statistics, covering a range of topics in modeling and analysis of data including: review of simple linear regression, twosample problems, oneway analysis of variance; multiple linear regression, diagnostics and model selection; twoway analysis of variance, multiple comparisons, and other
selected topics. Three hours of lecture supplemented by one and onehalf hours of laboratory.
STATS 405 / ECON 405. Introduction to Statistics.
Section 001.
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). May not be repeated for credit.
Credits: (4).
Course Homepage: No homepage submitted.
The purpose of this course is to provide students with an understanding of the
principles of statistical inference. Topics include probability, experimental and
theoretical derivation of sampling distributions, hypothesis testing, estimation, and simple regression. (Students are advised to elect the sequel, ECON 406.)
TEXTBOOK:
Statistics: Theory and Methods,
Berry/Lindgren,
2nd Edition.
STATS 408. Statistical Principles for Problem Solving: A Systems Approach.
Section 001.
Prerequisites & Distribution: High school algebra. No credit granted to those who have completed or are enrolled in STATS 170. (4). (Excl). (BS). May not be repeated for credit.
Credits: (4).
Course Homepage: http://coursetools.ummu.umich.edu/2003/winter/stats/408/001.nsf
Our purpose is to help students use quantitative reasoning to facilitate learning.
Specifically, we introduce statistical and mathematical principles, and then use these as analogues in a variety of real world situations. The notion of a system, a collection of components that come together repeatedly for a purpose, provides an excellent framework to describe many real world phenomena and provides a way to view the quality of an inferential process.
Evaluation is focused on clear writing that illustrates understanding of the theory by providing new applications of the theory. Points are obtained from four activities: a journal (max 20 points); test score (max 30 points); and discussion section leader bonus (max 5 additional points).
TEXTBOOKS:
 Theory of Constraints,
E. Goldratt,
Northriver Press;
 The Goal,
E. Goldratt,
Northriver Press;
 The Fifth Discipline,
Peter M. Senge,
Doubleday Currency; and
 The New Economics for Industry Government Education,
W. Edwards Deming,
2nd Edition,
MIT.
STATS 412. Introduction to Probability and Statistics.
Section 001.
Instructor(s):
Elizaveta Levina
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). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~elevina/stat412/index.html
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). May not be repeated for credit.
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). May not be repeated for credit.
Credits: (3).
Course Homepage: http://wwwpersonal.umich.edu/~jrs/math425.html
See Mathematics 425.001.
STATS 425 / MATH 425. Introduction to Probability.
Section 002.
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.math.lsa.umich.edu/~sadovska/425/425.html
See Mathematics 425.002.
STATS 425 / MATH 425. Introduction to Probability.
Section 003.
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.math.lsa.umich.edu/~kalinin/Teach/425/425index.html
See Mathematics 425.003.
STATS 425 / MATH 425. Introduction to Probability.
Section 007 – Section 007 ONLY satisfies the upperlevel writing requirement.
Instructor(s):
Burns Jr
Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: No homepage submitted.
See Mathematics 425.007.
STATS 426. Introduction to Theoretical Statistics.
Section 001.
Prerequisites & Distribution: STATS 425. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~moulib/stat426win03.html
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 STATS 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

 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 466 / IOE 466 / MFG 466. Statistical Quality Control.
Section 001.
Instructor(s):
Prerequisites & Distribution: STATS 265 and 401 or IOE 366. (4). (Excl). (BS). CAEN lab access fee required for nonEngineering students. May not be repeated for credit.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://coursetools.ummu.umich.edu/2003/winter/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, specifications and tolerances, gage capability studies, acceptance sampling by attributes and variables, international quality standards.
STATS 480. Survey Sampling Techniques.
Section 001.
Prerequisites & Distribution: STATS 350. (4). (Excl). (BS). May not be repeated for credit.
Credits: (4).
Course Homepage: No homepage submitted.
Introduces students to basic ideas in survey sampling, moving from motivating examples to abstraction to populations, variables, parameters, samples and sample design, statistics, sampling distributions, HorvitzThompson estimators, basic sample design (simple random, cluster, systematics, multiple stage), various errors and biases, special topics. There will be weekly assignments and a final exam. Class format is three hours of lecture and one hour of laboratory per week.
STATS 499. Honors Seminar.
Instructor(s):
Prerequisites & Distribution: Permission of departmental Honors advisor. (23). (Excl). (INDEPENDENT). May not be repeated for credit.
Credits: (23).
Course Homepage: No homepage submitted.
Advanced topics, reading and/or research in applied or theoretical statistics.
STATS 501. Applied Statistics II.
Section 001.
Prerequisites & Distribution: STATS 500. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~faraway/stat501/
Generalized Linear Models, Analysis of binary and categorical data, Loglinear models, Random and mixed effects models, Smoothing and nonparametric regression, Generalized Additive models, Regression and classification trees, Neural Networks.
Course pack.
The following books are recommended
 Generalized Linear Models by Nelder & McCullagh (2nd Ed, Chapman Hall),
 Applying Generalised Linear Models by Lindsey (Springer),
 Modelling Binary Data by Collett (Chapman Hall)
 Categorical Data Analysis by Agresti (Wiley),
 Generalized Additive Models by Hastie & Tibshirani (Chapman Hall)
Assessment:
Assignments worth 30%;
Midterm worth 30%;
Final worth 40%.
All examinations are open book.
STATS 525 / MATH 525. Probability Theory.
Instructor(s):
Sadovskaya
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). May not be repeated for credit.
Credits: (3).
Course Homepage: No homepage submitted.
See Mathematics 525.001.
STATS 526 / MATH 526. Discrete State Stochastic Processes.
Section 001.
Instructor(s):
Prerequisites & Distribution: STATS 525 or EECS 501. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: No homepage submitted.
See Mathematics 526.001.
STATS 531 / ECON 677. Analysis of Time Series.
Section 001.
Instructor(s):
Edward L Ionides
Prerequisites & Distribution: STATS 426. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~ionides/531/
Decomposition of series; trends and regression as a special case of time series; cyclic components; smoothing techniques; the variate difference method; representations including spectrogram, periodogram, etc.; stochastic difference equations, autoregressive schemes, moving averages; large sample inference and prediction; covariance structure and spectral densities; hypothesis testing, estimation, and applications, and other topics.
STATS 535 / IOE 562. Reliability.
Section 001.
Prerequisites & Distribution: STATS 425 and 426 (or IOE 316 and 366). (3). (Excl). (BS). CAEN lab access fee required for nonEngineering students. May not be repeated for credit.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.stat.lsa.umich.edu/~vnn/ioe562/index.html
This course will cover the important reliability concepts and methodology that arise in modeling, assessing and improving product reliability and in analyzing field and warranty data. Topics will be selected from the following:
 Basic reliability concepts;
 Common parametric models for component reliability;
 Censoring schemes;
 Analysis of timetofailure data;
 Accelerated testing for reliability assessment;
 Modeling and analyzing repairable systems reliability;
 Analysis of warranty and fieldfailure data;
 Maintenance policies and availability;
 Reliability improvement through experimentation.
STATS 550 / IOE 560 / SMS 603. Bayesian Decision Analysis.
Section 001.
Instructor(s):
Stephen M Pollock
Prerequisites & Distribution: STATS 425. (3). (Excl). (BS). CAEN lab access fee required for nonEngineering students. May not be repeated for credit.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://coursetools.ummu.umich.edu/2003/winter/ioe/560/001.nsf
Topics:
 Axiomatic foundations for, and assessment of, probability and utility;
 formulation of decision problems;
 risk functions, admissibility;
 likelihood functions and the likelihood principle;
 natural conjugate a priori distributions;
 Bayesian regresion analysis and hypothesis testing;
 hierarchical models;
 credible intervals;
 numerical analysis;
 applications to decisionmaking.
STATS 576 / ECON 679. Econometric Theory II.
Section 001.
Prerequisites & Distribution: STATS 575. (3). (Excl). (BS). May not be repeated for credit.
Credits: (3).
Course Homepage: http://www.econ.lsa.umich.edu/~ssakata/courses/info/econ679/syllabus.html
See Economics 679.001.
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