Transfer Student Courses in Statistics These pages are no longer maintained. Consult the new Course Guide at: http://www.lsa.umich.edu/lsa/cg_subjectlist/0,2030,8,00.html?show=20&termArray=f_04_1510&cgtype=ug This page was created at 12:42 PM on Wed, May 5, 2004. Fall Academic Term, 2004 (September 7 - December 23) Search Only the Transfer Student LS&A Course Guide (Advanced Search Page) Search the Full LS&A Course Guide (Advanced Search Page) STATS 100. Introduction to Statistical Reasoning. Instructor(s): Prerequisites & Distribution: (4). (MSA). (BS). (QR/1). May not be repeated for credit. 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. Credits: (4). Course Homepage: No homepage submitted. 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). Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 265 / IOE 265. Probability and Statistics for Engineers. Section 001. Instructor(s): Luis Manuel Garcia-Guzman Prerequisites & Distribution: MATH 116 and ENGR 101. (4). (Excl). (BS). May not be repeated for credit. No credit granted to those who have completed or are enrolled in STATS 311, 400, 405, or 412, or ECON 405. CAEN lab access fee required for non-Engineering students. Credits: (4). Lab Fee: CAEN lab access fee required for non-Engineering students. Course Homepage: No homepage submitted. 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 course 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., IOE 316, 366, 421, 425, 432, 441, 447, 449, 452, 460, 463, 465, 466, 474, 424/491). Text: 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 closed-book 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 double-sided 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 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 350. Introduction to Statistics and Data Analysis. Instructor(s): Prerequisites & Distribution: (4). (NS). (BS). (QR/1). May not be repeated for credit. 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. Credits: (4). Course Homepage: No homepage submitted. 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 analysis-computer package. Course evaluation is based on a combination of two examinations, a final examination, weekly homework, and lab participation. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 400. Applied Statistical Methods. Section 001. Instructor(s): Prerequisites & Distribution: High School Algebra. (4). (Excl). (BS). (QR/1). May not be repeated for credit. No credit granted to those who have completed or are enrolled in ECON 404 or 405, or STATS 250, 265, 350, 405, or 412. 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; one-sample tests of hypothesis; two-sample problems; analysis of variance (ANOVA); blocked designs; tests for association and independence (chi-square tests); regression and correlation; and non-parametric tests. Course format includes lectures (3 hours per week) and a laboratory (1.5 hours per week). Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 425 / MATH 425. Introduction to Probability. Instructor(s): STATISTICS FACULTY 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. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 425 / MATH 425. Introduction to Probability. Instructor(s): MATHEMATICS FACULTY Prerequisites & Distribution: MATH 215, 255, or 285. (3). (Excl). (BS). May not be repeated for credit. Credits: (3). Course Homepage: No homepage submitted. See MATH 425. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 466 / IOE 466 / MFG 466. Statistical Quality Control. Section 001. Instructor(s): Jianjun Shi Prerequisites & Distribution: STATS 265 and 401 or IOE 366. (3). (Excl). (BS). May not be repeated for credit. CAEN lab access fee required for non-Engineering students. Credits: (3). Lab Fee: CAEN lab access fee required for non-Engineering 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. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. STATS 535 / IOE 562. Reliability. Section 001. Instructor(s): Prerequisites & Distribution: STATS 425 and 426 (or IOE 316 and 366). (3). (Excl). (BS). May not be repeated for credit. CAEN lab access fee required for non-Engineering students. Credits: (3). Lab Fee: CAEN lab access fee required for non-Engineering students. Course Homepage: No homepage submitted. No Description Provided. Contact the Department. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 1 STATS 550 / IOE 560 / OMS 603. Bayesian Decision Analysis. Section 001. Instructor(s): Stephen M Pollock Prerequisites & Distribution: STATS 426 OR IOE 366. (3). (Excl). (BS). May not be repeated for credit. CAEN lab access fee required for non-Engineering students. Business School Network fee may be required for non-Business students. Credits: (3). Lab Fee: CAEN lab access fee required for non-Engineering students. Business School Network fee may be required for non-Business students. Course Homepage: No homepage submitted. 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 decision-making. Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given. These pages are no longer maintained. Consult the new Course Guide at: http://www.lsa.umich.edu/lsa/cg_subjectlist/0,2030,8,00.html?show=20&termArray=f_04_1510&cgtype=ug This page was created at 12:42 PM on Wed, May 5, 2004. University of Michigan | College of LS&A | Student Academic Affairs | LS&A Bulletin Index | Department Homepage This page maintained by LS&A Advising Technology (webmaster_saa@umich.edu), G255-E Angell Hall Copyright © 2004 The Regents of the University of Michigan, Ann Arbor, MI 48109 USA +1 734 764-1817 Trademarks of the University of Michigan may not be electronically or otherwise altered or separated from this document or used for any non-University purpose.