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Open courses in Statistics
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Wolverine Access Subject listing for STATS
Winter Term '01 Time Schedule for Statistics.
STATS 100. Introduction to Statistical Reasoning.
Section – MIDTERM EXAM ON THURSDAY,FEBRUARY 22, 68 P.M.
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Soc. 210, Stat. 250, 350, 402, 405, or 412, or Econ. 404 or 405. (4). (MSA). (BS). (QR/1).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/class/stat100/
This course will provide an overview of the field of Statistics. It will expose students to statistical reasoning and concepts for dealing with uncertainty, visualizing and analyzing data, and drawing conclusions from experimental or observational data. Emphasis is on presenting underlying concepts rather than covering a variety of different methodologies. Course evaluation is based on a combination of inclass quizzes, weekly homework, a Thursday evening midterm examination, a final examination, and GSI input. The course format includes lectures and a discussion section (1 hour per week)
Homework
There will be weekly homework assignments, available each Monday on the web, which will be
collected and graded. Problems assigned (and their corresponding solutions) will be posted on the web
for viewing and printing.
There will be four inclass quizzes during the semester.
Textbook:
Interactive Statistics
Aliaga/Gunderson
PrenticeHall
Student Solutions Manual
TI83 Calculator – *Required.*
STATS 125. Games, Gambling and Coincidences.
Section 001.
Prerequisites & Distribution: Only firstyear students, including those with sophomore standing, may preregister for FirstYear Seminars. All others need permission of instructor. (3). (MSA). (QR/1).
FirstYear Seminar,
Credits: (3).
Course Homepage: No Homepage Submitted.
This course will emphasize problem solving and modeling. Students will work together in class attempting to solve various problems. With guidance from the instructor, students will create models and deduce the basic concepts necessary for solution. Students will be asked to write up solutions and work on a project. Grades will be determined from this work and class participation. Problems from the course will be drawn primarily from Markov chains with a finite state space, dynamic programming, again with a finite state space, and game theory. Possible examples include: gambler's ruin; expected run lengths in coin tossing until a specified string is obtained and chances that one string will occur before another; optimal strategies in sports and gambling; optimal replacement strategies; minimax solutions for finite state twoperson zero sum games.
NO TEXTBOOK
STATS 170. The Art of Scientific Investigation.
Section 001 – Meets with Statistics 408.001.
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Statistics 408. (4). (MSA). (BS). (QR/1).
Credits: (4).
Course Homepage: No Homepage Submitted.
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).
TEXTBOOK:
The Fifth Discipline Peter M. Senge.
Doubleday Currency
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 Engin. 101. No credit granted to those who have completed or are enrolled in Stat. 311, 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: http://wwwpersonal.engin.umich.edu/~goovaert/cours4.html
Engineering is divided into two worlds: deterministic and probabilistic. Your math, physics, and chemistry course preparation to date has concentrated on "deterministic" models: a given set of inputs or conditions repeatedly produce a fixed, completely predictable output. IOE 265 launches your modeling skills into a totally new dimension... the much more realistic situation wherein a given set of inputs or conditions produce random (or "chance" or "probabilistic" or "stochastic" ) outcomes! Examples include the characteristics of products leaving
manufacturing lines (e.g., lifetime of a bulb, concentration of a therapeutic drug), results of laboratory experiments (e.g., growth rates of
microorganisms) or processes observed over space or time (e.g., spatial distribution of soil contaminants or time series of rainfall amounts). The
field of statistics deals with the collection, presentation, analysis and use of data to make decisions, solve problems and design products and processes.
The first part of the class will be devoted to the presentation of probabilistic concepts which are the building blocks of all statistical procedures that will be introduced in the second (more applied) part of the class. Homeworks and labs will allow students to apply these concepts and learn how to use basic statistical Excel functions to solve problems.
The course prerequisites are Math 116 and Engin 101. IOE 265 is a prerequisite for many undergraduate IOE courses (e.g., 316, 366, 421, 425, 432, 441, 447, 449, 452, 460, 463, 465, 466, 474, 424/491).
Applied Statistics and Probability for Engineers by Douglas C. Montgomery and George C. Runger, Second Edition, 1998. Chapters 1 to 9 will be covered in this course.
Grading scheme:
 Homeworks: 30% Homeworks will typically be assigned on a Wednesday and are due on Friday the next week, see schedule below. A dropping time and place will
be specified later. Solutions to homework problems will be posted on this Website and CAEN Website the day after the due date, hence late homeworks will receive no credit. According to the Engineering Honor Code, all homework assignments are to be completed on your known, without using solutions prepared in prior years. Two lab sessions will be devoted to Technical communication and the related assignment will be
graded and counted as homework #11.
 2 midterm Exams: 40%
 Final Exam: 30% All exams will be closedbook and will consist of a set of multiple choice questions and problems covering both theory and applications. For
each midterm, you may use, however, 1 crib sheet (two sides) including all information that you think may be helpful in the examination.
The final exam will be comprehensive and 3 doublesided crib sheets will be permitted.
Course outline:
 Data Summary and Presentation
 Concepts of sample and population
 Type of data
 Descriptive statistics
 Data summary and display
 Probabilistic Concepts
 Sample spaces and events
 Axioms of probability
 Conditional probability and independence
 Random variables: discrete and continuous
 Probability Distributions
 Probability mass(density) functions and cumulative distribution functions
 Mean and variance of a random variable (RV)
 Examples of probability distributions
 Discrete RV: uniform, binomial, (hyper)geometric, Poisson
 Continuous RV: Normal, exponential, Gamma, Weibull
 Joint probability distributions
 Parameter Estimation
 Properties of estimators
 Estimation methods
 Sampling distributions & confidence intervals
 Statistical inference
 Hypothesis testing
 Inference on the mean and variance
 Inference on a population proportion
 Goodness of Fit
 Inference for two samples
STATS 350(250/402). Introduction to Statistics and Data Analysis.
Section – TWO (2) WEDNESDAY EVENING MIDTERM EXAMINATIONS FOR STATISTICS 402 ON 02/14 AND 3/28, 68 P.M.
Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Econ. 404 or 405, or Stat. 250, 265, 311, 400, 402, 405, or 412. (4). (NS). (BS). (QR/1).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/class/stat350/
In this course students are introduced to the concepts and applications of statistical methods and data analysis. Statistics 250 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 subjectmatter. 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 midterm examinations, a final examination, weekly homework, and lab participation.
This course was previously Stats 402. Advanced undergraduates and graduate students should take the new course, Stats 400.
Homework
There will be weekly homework assignments and weekly computer lab work. Problems assigned (and their
corresponding solutions) will be posted and available on the web for printing. Scientific Notebook Viewer is
needed for viewing and printing solutions. Download instructions are available on the web (under Latest
News).There are two semester exams and a Final exam.
Grading Policy:
Performance on exams will account for 90% of your final grade and homework/lab attendance and participation will account for 10%.
Textbook: (required) Introduction to the Practice of Statistics
Authors: Moore and McCabe, Freeman, 1999
Computer Modules: (required) Statistics 350 (250) Workbook, Winter 2001
HaydenMcNeil Publishing Inc., 2000 ISBN: 0738004057
SPSS 6.1 (Student Version) (Mac)
SPSS 6.1 (Student Version) (Word)
Lecture Notes: (optional – used with Prof. Gunderson and Prof. Kapatou's sections only) Winter 2001
HaydenMcNeil Publishing Inc., 2000 ISBN: 0738003239
STATS 400. Applied Statistical Methods.
Section 001.
Prerequisites & Distribution: High School Algebra. No credit granted to those who have completed or are enrolled in Econ. 404 or 405, or Stat. 250, 350, 265, 402, 405, or 412. (4). (Excl). (BS).
Credits: (4).
Course Homepage: http://www.stat.lsa.umich.edu/~dbingham/Stat400/index.html
This course is aimed at advanced undergraduate students and graduate students from disciplines outside of Statistics. The course will introduce students to a broad range of applied statistical methods involved in data collection, analysis and visualization. Emphasis will be placed on using statistical methods to answer realworld problems. 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).
TEXTBOOK:
Statistics: Principles and Methods
Johnson/Bhattacharyya
4th Edition
ISBN: 0471388971
Wiley.
STATS 400. Applied Statistical Methods.
Section 002.
Instructor(s): Alexandra Kapatou
Prerequisites & Distribution: High School Algebra. No credit granted to those who have completed or are enrolled in Econ. 404 or 405, or Stat. 250, 350, 265, 402, 405, or 412. (4). (Excl). (BS).
Credits: (4).
Course Homepage: No Homepage Submitted.
No Description Provided
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STATS 403. Introduction to Statistics and Data Analysis II.
Section 001.
Prerequisites & Distribution: Stat. 350 (or 402). (4). (Excl). (BS).
Credits: (4).
Course Homepage: No Homepage Submitted.
Intermediate topics in multiple linear regression and the analysis of variance, stressing applications: least squares estimates, test of hypotheses, prediction analysis, residual analysis, multicollinearity, and the variable selection techniques; fixed and random effects models in ANOVA; multiple comparisons, randomized blocks, Latin squares, nested and hierarchical designs; and robust procedures, as time permits. Three hours of lecture supplemented by one and onehalf hours of laboratory.
TEXTBOOK:
Modern Regression Methods
Thomas P. Ryan
Wiley
ISBN: 0471529125.
STATS 405/Econ. 405. Introduction to Statistics.
Section 001.
Prerequisites & Distribution: Math. 116 or 118. 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 Stat. 265, 311 or 412. Students with credit for Econ. 404 can only elect Stat. 405 for 2 credits and must have permission of instructor. (4). (MSA). (BS). (QR/1).
Credits: (4).
Course Homepage: No Homepage Submitted.
See Economics 405.001.
STATS 408. Statistical Principles for Problem Solving: A Systems Approach.
Section 001 – Meets with Statistics 170.001.
Prerequisites & Distribution: High School Algebra. No credit granted to those who have completed or are enrolled in Statistics 170. (4). (Excl). (BS).
Credits: (4).
Course Homepage: No Homepage Submitted.
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.
Reading Materials Include: "The New Economics," 2nd Edition; W. Edwards Deming; "The Fifth Discipline," Peter Senge; "The Goal," Eliyahu Goldratt; "Theory of Constraints," Eliyahu Goldratt. 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: (1) a journal (max 20 points); (3) test score (max 30 points); (4) discussion section leader bonus (max 5 additional points).
TEXTBOOK:
Theory of Constraints
E. Goldratt
Northriver Press
The Goal
E. Goldratt
Northriver Press
The Fifth Discipline
Peter M. Senge
Doubleday Currency
The New Economics for Industry Government Education
W. Edwards Deming
2nd Edition
MIT
STATS 412. Introduction to Probability and Statistics.
Section 001.
Prerequisites & Distribution: Prior or concurrent enrollment in Math. 215 and CS 183. No credit granted to those who have completed or are enrolled in Econ. 405, or Stat. 265, 311, 350, 400, or 405. One credit granted to those who have completed Stat. 250 or 402. (3). (MSA). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~wangxiao/412.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.
Section 001.
Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
Sample spaces and axiomatic probability; elementary combinatorics; conditional probability and independence; random variables; probability distributions, including binomial, Poisson, Gamma, and normal; expectation, mean and variance; moment generating functions; the law of large numbers; central limit theorem.
TEXTBOOK:
A First Course in Probability
Sheldon Ross
5th Edition
PrenticeHall
ISBN: 0137463146.
STATS 425/Math. 425. Introduction to Probability.
Section 002, 003, 006.
Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
See Mathematics 425.002.
STATS 425/Math. 425. Introduction to Probability.
Section 004, 005.
Instructor(s): Yanhong Wu
Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
Sample spaces and axiomatic probability; elementary combinatorics; conditional probability and independence; random variables; probability distributions, including binomial, Poisson, Gamma, and normal; expectation, mean and variance; moment generating functions; the law of large numbers; central limit theorem.
TEXTBOOK:
A First Course in Probability
Sheldon Ross
5th Edition
PrenticeHall
ISBN: 0137463146.
STATS 425/Math. 425. Introduction to Probability.
Section 006.
Instructor(s): P Jeganathan
Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
No Description Provided
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STATS 426. Introduction to Mathematical Statistics.
Section 001.
Prerequisites & Distribution: Stat. 425. (3). (MSA). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~dhkim/426.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 Statistics 425/426 serves as a prerequisite for more advanced Statistics courses, regular homework and a final exam.
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
Text: Mathematical Statistics and Data Analysis by John Rice
STATS 430. Applied Probability.
Section 001.
Prerequisites & Distribution: Stats. 425. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
No Description Provided
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STATS 466/IOE 466/Manufacturing 466. Statistical Quality Control.
Section 001.
Prerequisites & Distribution: Stat. 265 and Stat 403 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://www.engin.umich.edu/class/ioe466/
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; charting, smoothing, forecasting, and prediction of discrete time series.
Text:
"Introduction to Statistical Quality Control", 3rd edition, D.C. Montgomery, Wiley & Sons, 1996.
"Lecture Notes Coursepack", Art and Architecture Copy Center
STATS 480. Survey Sampling Techniques.
Section 001.
Prerequisites & Distribution: Stat. 350 (or 402). (4). (Excl). (BS).
Credits: (4).
Course Homepage: No Homepage Submitted.
Course will introduce 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 designs (simple random, cluster, systematic, stratified, multiple state), various errors and biases, special topics. Three hours lecture and 1.5 hour laboratory session each week.
TEXTBOOK:
Sampling: Design and Analysis
Sharon L. Lohr
Duxbury
ISBN: 0534353614
STATS 499. Honors Seminar.
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 501. Applied Statistics II.
Section 001.
Prerequisites & Distribution: Stat. 500. (3). (Excl). (BS).
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 511. Mathematical Statistics II.
Section 001.
Prerequisites & Distribution: Stat. 510. (3). (Excl). (BS).
Credits: (3).
Course Homepage: http://www.stat.lsa.umich.edu/~keener/511/index.html
Topics covered will include: hypothesis testing and related topics such as size, power, similarity and optimality properties. Likelihood ratio tests, generalized likelihood ratio tests, decision theory, and Bayes approaches. Sequential procedures, large sample theory, and various other topics.
TEXTBOOK:
Course Notes
Testing Statistical Hypothesis [recommended]
E. L. Lehmann
2nd Edition
SpringerVerlag
ISBN: 0387949194
STATS 525/Math. 525. Probability Theory.
Section 001.
Prerequisites & Distribution: Math. 450 or 451. Students with credit for Math. 425/Stat. 425 can elect Math. 525/Stat. 525 for only one credit. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
See Mathematics 525.001.
STATS 526/Math. 526. Discrete State Stochastic Processes.
Section 001.
Prerequisites & Distribution: Stat. 525 or EECS 501. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
See Statistics 526.001.
STATS 531/Econ. 677. Analysis of Time Series.
Section 001.
Prerequisites & Distribution: Stat. 426. (3). (Excl). (BS).
Credits: (3).
Course Homepage: No Homepage Submitted.
Models and methods for univariate and multivariate discrete
time stochastic processes; estimation, testing, and forecasting; frequency domain methods; applications of the Kalman filter.
TEXTBOOK:
Time Series Analysis
Hamilton
1994 Edition
Princeton University Press
ISBN: 0691042896
This page was created at 7:24 PM on Mon, Jan 29, 2001.
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