Statistics (M.S.)  Graduate (Combined B.S. Math/M.S.)  2015 University Catalog
STATISTICS (Combined Bs/Ms)
Complete 33 semester hours including the following 4 requirement(s): (9 hours will be applied from the UG program)

STATISTICS CORE
Complete the following 15 semester hours: .
STAT 542 Statistical Theory I (3 hours lecture) 3 STAT 543 Statistical Theory II (3 hours lecture) 3 STAT 544 Statistical Computing (3 hours lecture) 3 STAT 547 Design and Analysis of Experiments (3 hours lecture) 3 STAT 548 Applied Regression Analysis (3 hours lecture) 3 
Statistics Electives

Complete 3 semester hours from the following list
STAT 640 Biostatistics I (3 hours lecture) 3 STAT 646 Multivariate Analysis (3 hours lecture) 3 STAT 648 Advanced Statistical Methods (3 hours lecture) 3 
Complete 9 semester hours from the following list
STAT 545 Practicum in Statistics I 3 STAT 546 NonParametric Statistics (3 hours lecture) 3 STAT 549 Sampling Techniques (3 hours lecture) 3 STAT 552 Intermediate Statistics Methods (3 hours lecture) 3 STAT 561 Statistical Data Mining I (3 hours lecture) 3 STAT 562 Statistical Data Mining II (3 hours lecture) 3 STAT 570 Statistical Consulting (3 hours lecture) 3 STAT 583 Fundamentals of Data Analysis (3 hours lecture) 3 STAT 595 Topics in Statistics (3 hours lecture) 3 STAT 597 Research Methods in Statistical Science (3 hours lecture) 3


Comp Sci, Math, and/or Stat Electives
Complete the following 6 semester hours:
STAT 552 Intermediate Statistics Methods (3 hours lecture) 3 STAT 597 Research Methods in Statistical Science (3 hours lecture) 3 
CULMINATING EXPERIENCE
Complete one of the following options:

THESIS OPTION
Complete STAT 698 as a Statistical or Other Elective. Submit thesis hardcopy to Graduate Adm & Support Services.

COMPREHENSIVE EXAMINATION
In the term that you will sit for exam, register for  which matches your major & advisor. Successfully pass exam.
GRAD CMP Comprehensive Examination 0

Course Descriptions:
GRADCMP: Comprehensive Examination
This course is a placeholder for matriculated master's students planning to take the departmental Comprehensive Examination. Successful completion of the Comprehensive Examination will result in a grade of P, unsuccessful students will receive a grade of NC. Students who do not successfully complete the Comprehensive Examination will be required to register for this placeholder course in each term for which they plan to take the examination (limited to three). 0 sh.
Prerequisites: Matriculation in Master's degree program required.
STAT542: Statistical Theory I (3 hours lecture)
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chisquared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, NeymanPearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.
Prerequisites: STAT 541 and permission of graduate program coordinator.
STAT543: Statistical Theory II (3 hours lecture)
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chisquared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, NeymanPearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.
Prerequisites: STAT 542 and permission of graduate program coordinator.
STAT544: Statistical Computing (3 hours lecture)
Computer systems for data analysis and data graphics, and intermediate level statistical methodology are investigated. Several statistical computing packages are utilized and evaluated. 3 sh.
Prerequisites: STAT 541 or STAT 548, and CMPT 183, and permission of graduate program coordinator.
STAT545: Practicum in Statistics I
An applied experience in which students work with practitioners in industry, government or research organizations utilizing statistical techniques in a research setting. Students will work with statisticians on projects involving experimental design and data collection as well as the analysis and interpretation of the data. May be repeated once. 3 sh.
Prerequisites: STAT 541, STAT 544, and STAT 547 or STAT 548, and permission of graduate program coordinator.
STAT546: NonParametric Statistics (3 hours lecture)
Selected distributionfree tests and estimation techniques including sign, KolmogorovSmirnov, Wilcoxon signed rank, MannWhitney, Chisquare, rank correlation, Kendall's Tau, KruskalWallace, Friedman, McNemar, and others. 3 sh.
Prerequisites: STAT 330 and permission of graduate program coordinator.
STAT547: Design and Analysis of Experiments (3 hours lecture)
Fundamental principles of design; fixed, random and mixed models; factorial designs; designs with restricted randomization; splitplot design; confounding; fractional replication; experimental and sampling errors. 3 sh.
Prerequisites: STAT 541 or STAT 548, and permission of graduate program coordinator.
STAT548: Applied Regression Analysis (3 hours lecture)
Fitting equations to data; matrices, linear regression; correlation; analysis of residuals; multiple regression; polynomial regression; partial correlation; stepwise regression; regression and model building; regression applied to analysis of variance problems; introduction to nonlinear regression. 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT549: Sampling Techniques (3 hours lecture)
Sampling and survey methodology; basic sampling theory; simple, stratified, random, cluster, systematic and area sampling. Sampling errors and estimation procedures. 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT552: Intermediate Statistics Methods (3 hours lecture)
Follow up to introductory statistical methods course. Principles of statistical inference; categorical data analysis; one and twoway anova; multiple linear regression; nonparametric methods; bootstrap methods. Examples from a wide variety of disciplines. Statistical software is used. 3 sh.
Prerequisites: STAT 330, permission of graduate program coordinator.
STAT561: Statistical Data Mining I (3 hours lecture)
Introduction to the concepts and applications of a variety of data mining methods. Data mining is the process of selecting, exploring, and modeling large amounts of data to uncover previously unknown patterns in the data. Statistical methods covered include classification and regression trees, predictive modeling, and unsupervised learning. Handson applications to data sets from diverse fields. Statistical software is used. 3 sh.
Prerequisites: STAT 541 or STAT 548 or equivalent, permission of graduate program coordinator.
STAT562: Statistical Data Mining II (3 hours lecture)
Continuation of STAT 561. An indepth approach to the topics of STAT 561 including logistic regression, decision trees, classifier theory, predictive modeling and unsupervised learning methods. Mathematical details of these techniques as well as the computational methods for their implementation. Handson applications to data sets from diverse fields. Statistical software is used. 3 sh.
Prerequisites: STAT 548 and STAT 561, permission of graduate program coordinator.
STAT570: Statistical Consulting (3 hours lecture)
An introduction to the statistical and interpersonal issues that arise in statistical consulting. Topics include communicating with scientists in other disciplines, technical writing and presentation, and statistical tools for consulting. Lectures center around real case studies presented by the instructor and invited speakers. Statistical software is used. Emphasis of the course is on the scientific, statistical, computational, and communication skills that a statistical consultant needs for interacting effectively with researchers from a wide range of disciplines. 3 sh.
Prerequisites: STAT 541 or equivalent, permission of graduate program coordinator.
STAT583: Fundamentals of Data Analysis (3 hours lecture)
Theory and application of statistical methods for data analysis in professional industrial areas such as business, manufacturing, biomedical and marketing. Exploratory data analysis; principles of statistical inference; design and analysis of observational studies and experiments; linear regression. Additional topics based on real examples from other disciplines would include biostatistical methods, multivariate analysis, time series analysis, and data mining. Statistical software is used. 3 sh.
Prerequisites: STAT 330 and permission of the Graduate Program Coordinator.
STAT595: Topics in Statistics (3 hours lecture)
Topics such as exploratory data analysis, statistical graphics, statistical quality control and statistical quality assurance, Bayesian methods and Markov chain Monte Carlo studies. May be repeated twice for a total of 9.0 credits. 3 sh.
Prerequisites: Permission of graduate program coordinator.
STAT597: Research Methods in Statistical Science (3 hours lecture)
Preparation for research in statistical science. Application of mathematics and computing science to the development, modeling, validation and evaluation of statistical research methods. Identification of statistical issues in real world problems and novel applications of statistical methods to these problems. Development of research proposals in statistical science. 3 sh.
Prerequisites: STAT 552 or equivalent and departmental approval.
STAT640: Biostatistics I (3 hours lecture)
Fundamental statistical concepts and methods used by statistical scientists in the health, biological, medical and pharmaceutical industries. Categorical data analysis, logistic regression, generalized linear models, nonparametric regression techniques. 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT646: Multivariate Analysis (3 hours lecture)
Analysis of multiple response variables simultaneously; covariance and the multivariate normal distribution; manova, discriminant functions; principle components and canonical correlations. 3 sh.
Prerequisites: STAT 541, STAT 548 and permission of graduate program coordinator.
STAT648: Advanced Statistical Methods (3 hours lecture)
Advanced statistical concepts and methods used by statistical scientists in the analysis of designed experiments and observational studies. Response surface methodology, analysis of covariance, the general linear model, the cell means model and the analysis of variance of unbalanced or messy data. 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.