Statistics

763-3519

Professor Robb Muirhead, Chair

May be elected as a departmental concentration program

Professors

Sandor Csorgo, Large sample theory, Probability and stochastic processes

William Ericson, Bayesian inference, sampling theory, statistical consulting

Bruce Hill, Bayesian inference, foundations, linear models

Phil Howrey (Economics), Econometrics, time series

Saul Hymans (Economics), Econometrics, macroeconomics

Robert W. Keener, Sequential analysis

Robb Muirhead, Asymptotic theory, classical inference, multivariate analysis

Vijayan Nair, Design and analysis of industrial experiments, quality improvement, reliability and censored data analysis, inference from biased sampling models, nonparametric methods, applied probability.

Ed Rothman, Applications, genetics

Keith Smith, Analysis of categorical data, experimental design

Michael Woodroofe, Classical inference, probability theory, sequential analysis

Chien-Fu Jeff Wu, Design and analysis of industrial experiments, quality improvement, experimental design, industrial statistics, statistical applications

Associate Professors

P. Jeganathan, Probability and stochastic processes, large sample theory

Assistant Professors

Julian J. Faraway, Adaptive estimation and smoothing, data analysis and statistical computing

Janis P. Hardwick, Data analysis and statistical computing, sequential analysis

Jiayang Sun, Projection pursuit, and sequential analysis

Prerequisites to Concentration. Mathematics 215 and 217; Computer Science 183

Concentration Program. Upon completion of the above prerequisite courses, the concentration program consists of at least 30 credits, additionally, in statistics, mathematics and electrical engineering and computer science courses. These 30 credits must include the following:

1. Statistics 425 and 426.

2. Statistics 402 and 413.

3. At least one of: Statistics 414, 470, or 480.

4. At least one 400+ level Mathematics course

5. At least once course in Electrical Engineering and Computer Science. This course will be EECS 283 or Statistics 406 or an advisor approved EECS course.

6. Elective courses in Statistics , Mathematics, or EECS. These are advisor approved electives. The list of approved courses include Statistics 406, 466, 470, 480, any 500+ level Statistics courses, and 300+ level advisor-approved EECS course and the Mathematics course in #4 above. (Math 216 does not qualify). Students interested in the application of statistics to various disciplines such as economics, biological sciences, and psychology are also encouraged to take courses in these areas.

Honors Concentration. Any student who has maintained an overall grade point average of at least 3.2 through the sophomore year may apply for admission to the Honors concentration program. Such application is made through the Department’s concentration advisor. Students in the Honors program must complete the regular concentration program above with at least a 3.5 GPA and must elect at least three of the following courses: Statistics 500, 501, 510, 511, and Mathematics 451 and 513. In addition, Honors concentrators must elect the Senior Honors Seminar or complete some project under the direction of a member of the faculty. This additional requirement should be arranged and discussed with the concentration advisor.

Advising. Normally, most statistics courses are elected after an introductory mathematics sequence has been completed or after consulting a department staff member. Advising appointments are made at 1444 Mason.

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Courses in Statistics (Division 489)

170(270). The Art of Scientific Investigation. (4). (NS).

290. The History of Chance. (3). (NS).

311/I.O.E. 365. Engineering Statistics. Engin. 103, Math. 215, and I.O.E 315 or Stat 310. No credit granted to those who have completed or are enrolled in Stat. 405 or 412. One credit granted to those who have completed Stat. 402. (4). (Excl).

402. Introduction to Statistics and Data Analysis. No credit granted to those who have completed or are enrolled in Econ. 404 or Stat. 311, 405, or 412. (4). (NS).

403. Introduction to Statistics and Data Analysis II. Stat. 402. (4). (Excl).

404. Problem Solving in Medical Statistics. Enrollment in Inteflex or permission of instructor. (3). (Excl).

405/Econ. 405. Introduction to Statistics. Math. 115 or permission of instructor. Juniors and seniors may elect concurrently with Econ. 201 and 202. No credit granted to those who have completed or are enrolled in Stat. 311 or 412. Students with credit for Econ. 404 can only elect Stat. 405 for 2 credits and must have permission of instructor. (4). (Excl).

406. Introduction to Statistical Computing. Stat. 425 and 402. (4). (Excl).

412. Introduction to Probability and Statistics. Prior or concurrent enrollment in Math. 215 and CS 183. No credit granted to those who have completed or are enrolled in 311 or 405. One credit granted to those who have completed Stat. 402. (3). (Excl).

413. The General Linear Model and Its Applications. Stat. 402 and Math. 217; concurrent enrollment in Stat. 425. Students who have not taken Math. 217 should elect Stat. 403. Two credits granted to those who have completed Stat. 403. (4). (Excl).

414. Topics in Applied Statistics. Stat 413 or 403; prior or concurrent enrollment in 426; and permission of instructor (4). (Excl).

425/Math. 425. Introduction to Probability. Math. 215. (3). (N.Excl).

426. Introduction to Mathematical Statistics. Stat. 425. (3). (NS).

466/IOE 466. Statistical Quality Control. Statistics 311 or IOE 365. (3). (Excl).

470. Experimental Design. Stat. 402. (4). (Excl).

480. Survey Sampling Techniques. Stat. 402. (4) (Excl).

499. Honors Seminar. Permission of departmental Honors advisor. (2-3). (Excl). (INDEPENDENT).

500. Applied Statistics I. Math. 417 and a course in statistics (Stat. 402 or 426); or permission of instructor. (3). (Excl).

501. Applied Statistics II. Stat. 500 or permission of instructor. (3). (Excl).

502. Analysis of Categorical Data. Stat. 426. (3). (Excl).

503. Applied Multivariate Analysis. Stat. 500 or permission of instructor. (3). (Excl).

504. Seminar on Statistical Consulting. Stat. 403 or 500. (1-4). (Excl). May be repeated for a total of 8 credits.

505/Econ. 673. Econometric Analysis. Permission of instructor. (3). (Excl).

506. Statistical Computing. Stat. 426 or 500, and CS 380 or 283, or permission of instructor. (3). (Excl).

510. Mathematical Statistics I. Math. 450 or 451, and a course in probability or statistics; or permission of instructor. (3). (Excl).

511. Mathematical Statistics II. Stat. 510. (3). (Excl).

525/Math. 525. Probability Theory. Math. 450 or 451; or permission of instructor. Students with credit for Math. 425/Stat. 425 can elect Math. 525/Stat. 525 for only 1 credit. (3). (Excl).

526/Math. 526. Discrete State Stochastic Processes. Math. 525, or Stat. 525, or EECS 501. (3). (Excl).

531/Econ. 677. Analysis of Time Series. Stat. 426. (3). (Excl).

550/SMS 576/I.O.E. 560. Bayesian Decision Analysis. Stat. 425 or permission of instructor. (3). (Excl).

551. Bayesian Inference. Stat. 550. (3). (Excl).

552. Sequential Analysis and Design. Stat. 426 or equivalent. (3). (Excl).

560/Biostat. 685 (Public Health). Introduction to Nonparametric Statistics. Stat. 426 or permission of instructor. (3). (Excl).

570. Experimental Design. Stat. 426 and a basic knowledge of matrix algebra; or permission of instructor. (3). (Excl).

575/Econ. 775. Econometric Theory I. Math. 417 and 425 or Econ. 653, 654, 673, and 674. (3). (Excl).

576/Econ. 776. Econometric Theory II. Econ. 775 or equivalent. (3). (Excl).