Professor Gunst, Department Chair
Professors: Bhat, Gray, Harris, Schucany, Stokes, Woodward; Associate Professor: Hietala; Assistant Professors: McGee, Natarajan, Ng; Emeritus Professors: Kapadia, Read.
Statistics is the science that specializes in the collection, analysis, and interpretation of data. Statistics is an exacting science, a discipline based on precise mathematical formulation and careful adherence to underlying theoretical principles. Applications of statistics are as diverse as the many disciplines that collect and analyze data, including business, engineering, and the natural, physical, and social sciences. From selecting the best medical treatment for a particular cancer to ascertaining whether or not there is a greenhouse-induced global warming trend, proper statistical analysis of data provides critical information needed for making important decisions. Because of its interdisciplinary nature, Statistical Science is an excellent double major or minor. www.smu.edu/statistics
Requirements for the B.S. Degree. The curriculum is designed to serve students seeking challenging careers in industry, government, and business as well as those preparing for graduate study in statistical science. The primary focus of the required coursework is an enhancement of an individual's skills in data analysis and the proper interpretation of quantitative information. With a proper choice of electives, the program permits a student to obtain sufficient preparation for graduate school admission.
MATH: 1337, 1338, 2339
One of the following: CSE 1340, ISOM 2308
Advanced Departmental Courses
STAT: 4340 or 5340, 4370, 5344, 5371, 5372, 5374, 5377, 5385
Electives 12 hours selected from the following
STAT: 2301 or 2331 (no more than one)
MATH: 2343 and courses numbered above 3000 (except Math Education and History)
CSE: 3360, 5361, 5369
ECO: 5350, 5352
Special Comments -- STAT 2301 or STAT 2331 should not be taken after any of the required Statistics courses.
The following courses are recommended for students intending to do graduate study in Statistics: MATH: 3353, 5338
Requirements for the Minor. The Statistical Science major is particularly useful to individuals in the sciences, engineering or applied sciences, social sciences, and business.
More generally, those planning careers that involve the processing, description, and/or analysis of data will find a minor in statistics beneficial.
A minor in Statistical Science requires 15 or more hours of statistics selected as indicated from the categories listed below.
1301. Introduction to Statistics. Introduction to collecting observations and measurements, organizing data, variability, and fundamental concepts and principles of decision-making. Emphasis is placed on statistical reasoning and the uses and misuses of statistics.
2301. Statistics for Modern Business Decisions. A foundation in data analysis and probability models is followed by elementary applications of condence intervals, hypothesis testing, correlation, and regression. Prerequisite: CEE Math Fundamentals or equivalent.
2331. Introduction to Statistical Methods. An introduction to statistics for behavioral, biological, and social scientists. Topics include descriptive statistics, probability and inferential statistics including hypothesis testing, analysis of variance, and contingency tables.
3300. Applied Statistical Data Analysis. This course emphasizes the analysis of data using state-of-the-art statistical methods and specialized statistical software. Case studies form a major component of the course requirements.
3341. Statistical Design and Analysis Experience. Fundamental principles and procedures for the statistical design of industrial and scientific experiments form the core of this course. Complete and fractional factorial experiments in completely randomized, randomized block, and nested designs are covered. The statistical analysis of these experiments, using appropriate statistical software, also will be emphasized.
4340 (CSE 4340). Statistical Methods for Engineers and Applied Scientists. Basic concepts of probability and statistics useful in the solution of engineering and applied science problems. Topics: probability, probability distributions, data analysis, sampling distributions, estimation, and simple tests of hypothesis. Prerequisites: MATH 1337 and 1338.
4370. Sampling Statistics. Simple random sampling; stratied, systematic, subsampling; means, variances, condence limits; nite population correction; sampling from binominal populations. Principles of planning and conducting surveys. Prerequisite: STAT 2301 or 2331, or permission of instructor.
These courses do not carry graduate credit for students in the M.S. program or in the Ph.D. program in statistics.
5340 (CSE 5370). Probability and Statistics for Scientists and Engineers. Introduction to fundamentals of probability and distribution theory, statistical techniques used by engineers and physical scientists. Examples of tests of signicance, operating characteristic curve, tests of hypothesis about one and two parameters, estimation, analysis of variance, and the choice of a particular experimental procedure and sample size. Prerequisites: MATH 1337, 1338, and 2339, or equivalent.
5344 (CSE 5364). Statistical Quality Control. Statistics and simple probability are introduced in terms of problems that arise in manufacturing; their application to control of manufacturing processes. Acceptance sampling in terms of standard sampling plans: MIL-STD 105, MIL-STD 414. Dodge-Romig plans, continuous sampling plans, etc. Prerequisite: STAT (CSE) 4340 or STAT 5340 (CSE 5370).
5371. Experimental Statistics. A non-calculus development of the fundamental procedures of applied experimental statistics, including tests of hypotheses and interval estimation for the normal, binomial, chi-square and other distributions, and nonparametric tests. Prerequisite: Junior standing or permission of instructor.
5372. Experimental Statistics. Analysis of variance, completely randomized design, randomized complete block designs-nested classications, factorials; analysis of covariance, simple and multiple linear regressions, and correlation. Prerequisite: STAT 5371.
5374. Theory of Probability and Statistics. Sums of random variables, sampling distributions, order statistics, estimation, hypothesis testing and its applications. Prerequisite: STAT (CSE) 4340 or STAT 5340 (CSE 5370).
5377. Statistical Design and Analysis of Experiments. Introduction to statistical principles in the design and analysis of industrial experiments. Completely randomized, randomized complete and incomplete block, Latin square, and Plackett-Burman screening designs. Complete and fractional factorial experiments. Descriptive and inferential statistics. Analysis of variance models. Mean comparisons. Prerequisite: STAT 4340 or 5371, or permission of instructor.
5385. Introductory Nonparametric Statistics. Introduction to nonparametric statistics with examples in the behavioral sciences, including choice and use of rank tests, runs tests and rank order correlation with tests given for one-sample and two-sample cases. Prerequisite: STAT 4340 or 5371 or 5340, or equivalent.