1440 Mason Hall
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C. F. Jeff Wu, Chair

May be elected as a departmental concentration program


Sandor Csórgö, Large sample theory, probability and stochastic processes
Bruce Hill, Bayesian inference, foundations, linear models
Phil Howrey (Economics), Econometrics, time series
Robert W. Keener, Sequential analysis
Roderick J. Little (Biostatistics), Missing data, survey sampling, applications of statistics
Robb Muirhead, Asymptotic theory, classical inference, multivariate analysis
Vijayan Nair, Industrial experiments, quality improvement, reliability, engineering statistics
Ed Rothman, Applications, genetics
Michael Woodroofe, Classical inference, probability theory, sequential analysis
Chien-Fu Jeff Wu, Experimental design, industrial statistics, computer-intensive methods, survey sampling

Associate Professors

Richard W. Andrews (Business Administration), Bayesian data analysis, statistical quality control
Julian J. Faraway, Adaptive estimation and smoothing, data analysis and statistical computing
P. Jeganathan, Probability and stochastic processes, large sample theory

Assistant Professors

S. G. Steven Kou, Categorical data analysis, statistics in finance, applied probability
Yingnian Wu, Modeling, statistical computing, computational vision


Brenda Gunderson, Applied multivariate analysis, applied statistics, statistical education

Adjunct Associate Professor

Martha B. Aliaga, Sequential analysis, statistical education, data 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 one course in Electrical Engineering and Computer Science. This course will be CS 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 1440 Mason Hall.

Courses in Statistics (Division 489)

100. Introduction to Statistical Reasoning. No credit granted to those who have completed or are enrolled in Soc. 210, Stat. 402, 311, 405, or 412, or Econ. 404. (4). (MSA). (BS). (QR/1).

125. Games, Gambling and Coincidences. (3). (MSA). (QR/1).

170. The Art of Scientific Investigation. (4). (MSA). (BS). (QR/1).

190(290). The History of Chance. (3). (NS). (BS).

311/IOE 365. Engineering Statistics. Engin. 103, Math. 215, and IOE 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). (BS).

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). (BS). (QR/1).

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

405/Econ. 405. Introduction to Statistics. 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. 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).

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

407. Data Analysis - A Computer Approach. Stat. 402. No credit granted to statistics undergraduate concentrators. (2). (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). (MSA). (BS).

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). (BS).

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

425/Math. 425. Introduction to Probability. Math. 215. (3). (MSA). (BS).

426. Introduction to Mathematical Statistics. Stat. 425. (3). (MSA). (BS).

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

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

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

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

500. Applied Statistics I. Math. 417, and Stat. 402 or 426. (3). (Excl). (BS).

501. Applied Statistics II. Stat. 500. (3). (Excl). (BS).

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

503. Applied Multivariate Analysis. Stat. 500. (3). (Excl). (BS).

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

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

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

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

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

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

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

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

550/SMS 576 (Business Administration)/IOE 560. Bayesian Decision Analysis. Stat. 425. (3). (Excl). (BS).

560/Biostat. 685 (Public Health). Introduction to Nonparametric Statistics. Stat. 426. (3). (Excl). (BS).

570. Experimental Design. Stat. 426 and a basic knowledge of matrix algebra. (3). (Excl). (BS).

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

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

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