Requirements for an Option-A Minor in Statistics

General Requirements for an Option-A Minor in Statistics:

For admission for an Option-A Minor in Statistics, the candidate must have had at least one year of calculus, and an introductory knowledge of Statistics that is satisfactory to the Department. Stat. 224, 201, or 301 or an equivalent course is sufficient for this purpose.
The minor must include one of the following series: Stat. 309, 310 or Stat. 311, 312 or Stat. 313, 314, or 609, 610 or 709, 710, plus a minimum of six credits in statistics chosen from other courses listed below in Group I. However, the candidate may choose three of these six credits from either Group II below or any other course in the University of suitable statistical content if approved by the Minor Program Advisor in the Department of Statistics. The courses taken by a particular student should depend on the student’s major field or individual needs.
The student should have a program of study approved by the Minor Program Advisor in the Department of Statistics and the student’s major professor, early in the student’s graduate work. The proposed program should be submitted to and approved by the Minor Program Advisor in Statistics before the six credits in excess of the required courses are taken.
The student must achieve a 3.00 GPA in courses used to satisfy the minor requirement.

Note: Candidates for an Option-A Minor in Statistics must be aware of the following Graduate School requirement according to which:

...One course (i.e., one semester course, and only one!) cross-listed with the major may be used for the minor so long as it is staffed by the minor department and is not applicable to any requirements for the major. For more information on the Graduate School requirements please go to Degrees, Minors & Certificates.

COURSES IN STATISTICS

Stat. 309 and 310 - Introduction to Mathematical Statistics (for majors in Mathematics & Statistics)
Stat. 311 and 312 - Introduction to Mathematical Statistics (for majors in Engineering, the Natural, Agricultural and Life Sciences)
Stat. 313 and 314 - Introduction to Mathematical Statistics (for majors in Business & Social Science)
Stat. 333 - Applied Regression Analysis
Stat. 349 - Introduction to Time Series
Stat. 351 - Introductory Non-Parametric Statistics
Stat. 411 - An Introduction to Sample Survey Theory and Methods
Stat. 421 - Applied Categorical Data Analysis
Stat. 424 - Statistical Experimental Design for Engineers
Stat. 456 - Applied Multivariate Analysis
Stat. 471 - Introduction to Statistical Data Processing
Stat. 542 - Introduction to Clinical Trials
Stat. 572 - Statistical Methods for Bioscience
Stat. 609 & 610 - Mathematical Statistics (MS level)
Stat. 641 - Statistical Methods for Clinical Trials
Stat. 642 - Statistical Methods for Epidemiology
Stat. 692 - Special Topics in Statistics
Stat. 701 & 702 - Applied Time Series Analysis - Forecasting and Control
Stat. 709 & 710 - Mathematical Statistics (Ph.D. level)
Stat. 732 - Large Sample Theory of Statistical Inference
Stat. 741 - Survival Analysis Theory & Methods
Stat. 749 &750 - Mathematical Models and Response Surface Methodology
Stat. 760 - Multivariate Analysis I
Stat. 761 - Multivariate Analysis II
Stat. 771 - Statistical Computing
Stat. 775 - Introduction to Bayesian Decision and Control
Stat. 803 - Experimental Design
Stat. 809 - Nonparametric Statistics
Stat. 811 - Sample Survey: Theory and Methodology
Stat. 824 - Nonlinear Regression Analysis
Stat. 826 - Theory of Life Testing and Reliability
Stat. 829 & 830 - Decision Theory
Stat. 840 & 841 - Continuous and Discrete Time Series
Stat. 842 - Hypothesis Testing
Stat. 849 & 850 - Analysis of Variance
Stat. 851 - Generalized Linear Models
Stat. 853 - Bayesian Inference
Stat. 860 - Topics in Time Series and Approximation Theory
Stat 992 - Seminar

SOME COURSES JOINTLY LISTED IN STATISTICS & MATHEMATICS OR STATISTICS AND COMPUTER SCIENCE

Math. 431 - Introduction to the Theory of Probability
Math. 475 - Introduction to Combinatorics
Math. 632 - Introduction to Stochastic Processes
Math. 726 - Non-linear Programming Methods
Math. 831 - Theory of Probability
Math. 832 - Topics in Probability
Math. 833 - Topics in Probability
Comp. Sci. 525 - Linear Programming Methods

APPLIED OPTION for the STATISTICS MINOR

The "Applied Statistics" Minor, for PhD students not in the Statistics Department, is designed to provide basic training in statistical methods to students whose background lacks calculus.(*) The requirements are a successful completion (that is, B or better in each course) of 12 or more credits selected from the following Statistics courses:

Stat. 302 - Introduction to Statistical Methods
Stat. 333 - Applied Regression Analysis
Stat. 349 - Introduction to Time Series
Stat.351 - Introduction to Non-parametric Statistics
Stat. 411 - Introduction to Sample Survey Theory and Methods
Stat. 421 - Applied Categorical Data Analysis
Stat. 424 - Statistical Experimental Design for Engineers
Stat. 456 - Applied Multivariate Analysis
Stat. 542 - Introduction to Clinical Trials
Stat. 572 - Statistical Methods for Bioscience II
Stat. 641 - Statistical Methods for Clinical Trials
Stat. 642 - Statistical Methods for Epidemiology
Stat. 692 - Special Topics in Statistics

Other upper division (7-800) statistics courses, subject to approval by the minor program advisor in statistics, can be used in place of these. Students with some undergraduate statistics preparation would not be able to count courses covering the material they have already completed. Requests for further information should be addressed to the faculty member acting as Minors Advisor in the Statistics Department. The name and telephone number of the current Minors Advisor is available from the Statistics Department Office; call 262-2598.

*Students with calculus backgrounds or from quantitative programs would normally take the Statistics Minor. The particular courses for this option are subject to approval from the minor advisor.

Revised 6/01