Mission Statement: The mission of the Department of Statistics is to provide students with a quality education in statistics, in which they acquire fundamental statistical skills and develop a sense of statistics as a profession. In addition, our graduates will be prepared for advanced studies in statistics and related disciplines, and for the diverse uses of statistics in business, industry, government, scientific research, and society.

Whether as a statistics major or a student in one of the department's numerous service courses, students receive training in critical thinking about sources of data, interpretation of data, and the merit of conclusions drawn from data. As all members of society are increasingly bombarded with information, the skills learned in the study of statistics contribute significantly to the development of enlightened members of society. The masters-level program offered by the Department of Statistics at The University of Akron is the only comprehensive programs in statistics at public institutions in the region. The research activities of faculty are primarily collaborative efforts with scientists and other researchers. These efforts have resulted in securing external grants, including federal funding.

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Admission Requirements:

Consideration for admission to the graduate program in statistics will be given to students who have (or are nearing completion of) a baccalaureate degree in statistics, mathematics, or a related area. A student with a degree in another discipline may be required to take prerequisite courses in mathematics or statistics as specified below.

All applicants for admission to the graduate program in statistics must meet the university requirements for graduate admission as published in the Graduate Bulletin of The University of Akron. All foreign graduate admissions require *TOEFL. In addition to meeting all University criteria for admission, the Department of Statistics requires three (3) current letters of reference, as well as completion of three semesters of Calculus, one semester of Linear Algebra and one semester of Applied Statistics (or equivalent). Applicants who have not taken the required prerequisite courses will be required to complete them prior to start of the program. The Department of Statistics does not require GRE or any other qualifying exam. Full admission is solely based upon the academic record and fulfillment of the required prerequisites with a minimum of gpa of 2.75 or 3.00 for the last two years (64 semester credits or equivalent). See Graduate Bulletin Section 2, General Information, Classification for further clarification.

*Foreign students from countries in which English is not the principal language must demonstrate proficiency in English by achieving a minimum score of 550 on the paper-based TOEFL or 79 or higher on the internet-based TOEFL (scores more than two years old will not be accepted) or a minimum score of 6.5 on the International English Language Testing System (IELTS) or successful passing the University of Akron Developed English Proficiency Test (UAdept) or successful completion of 24 credit hours of upper-level undergraduate or 18 credit hours of graduate course work at a U.S. university or college in which English is the primary language or successful completion of an undergraduate or graduate program at a university outside of the United States in which English is the language of administration and instruction. Applicants whose native language is not English and who expect to become teaching assistants are also required to achieve a minimum score of 50 on the Test of Spoken English (TSE) or achieve a 23 or greater on the speaking component of the internet-based TOEFL or pass other approved test as specified in the Graduate Bulletin Section 2, General Information, International Students, Admission for further clarification.

Financial Aid, Teaching and Research Assistantships:

The Department of Statistics has a number of graduate teaching assistantships available for qualified graduate students. These assistantships provide a waiver of all tuition (excluding fees) in addition to a bi-weekly stipend for half-time teaching or consulting duties. All foreign students must prove English speaking proficiency through one of the above means in order to be considered for a graduate teaching assistantship.

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The Department of Statistics offers the following degree options:

Master of Science - Statistics (with both Thesis and Nonthesis options)

Entrance into the program will require the initial completion of the following prerequisites:

Core curriculum (Effective Fall 2007):

Statistical Computer Science option (addition to existing master's program)

Thesis requirements (30 credits of graduate work)

• In addition to the core curriculum, 2-4 credits in 3470:699 Master's Thesis and 10-12 other approved elective graduate credit hours must be completed.
• Successful completion of the comprehensive examinations in the core curriculum.

Nonthesis requirements (33 credits of graduate work)

• In addition to the core curriculum, 2-4 credits in 3470-692 Statistics Masters Paper and 13-15 other approved elective graduate credit hours must be completed. The Statistical Computer Science option requirements may be applied toward the elective courses.
• Successful completion of the comprehensive examinations in the core curriculum.

3470: Course Descriptions

550 PROBABILITY (3 credits) - Prerequisite: Appropriate background is one semester of calculus or equivalent. Introduction to probability, random variables and probability distributions, expected value, sums of random variables, Markov processes.

551 THEORETICAL STATISTICS I and 552 THEORETICAL STATISTICS II (3 credits each) - Sequential. Prerequisite: Appropriate background is three semesters of calculus or equivalent. Elementary combinatorial probability theory, probability distributions, mathematical expectation, functions of random variables, sampling distributions, point and interval estimation, tests of hypotheses, regression and correlation, introduction to experimental designs.

560 STATISTICAL METHODS (4 credits) - Application of statistical methods to the social sciences including description statistics, probability distributions, statistical inference (parametric, nonparametric), categorical data analysis, linear regression, correlation, computer applications. May not be used to meet Mathematical Sciences degree requirements.

561 APPLIED STATISTICS (4 credits) - Prerequisite: Appropriate background is two semesters of calculus or equivalent. Applications of statistical theory to natural and physical sciences and engineering, including probability distributions, interval estimation, hypotheses testing (parametric and nonparametric), and simple linear regression and correlation.

562 APPLIED REGRESSION AND ANOVA (4 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Applications of the techniques of regression and multifactor analysis of variance.

565 DESIGN OF SAMPLE SURVEYS (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Design and analysis of frequently used sample survey techniques.

569 RELIABILITY MODELS (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Selected topics in reliability modeling including parametric and nonparametric models, competing modes of failure, censored data and accelerated life models.

571 ACTUARIAL SCIENCE I (3 credits) - Prerequisite: Appropriate background is two semesters of calculus or equivalent. Study of various statistical, financial, and mathematical calculations used to determine insurance premiums related to contingent risks based on individual risk model frameworks.

572 ACTUARIAL SCIENCE II (3 credits) - Prerequisite: 571. Continuation of Actuarial Science I. Study of multiple life functions, multiple decrement models, valuation theory for pension plans, insurance models including expenses, nonforfeiture benefits and dividends.

575 FOUNDATIONS OF STATISTICAL QUALITY CONTROL (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Course provides a solid foundation in the theory and applications of statistical techniques widely used in industry.

580 STATISTICAL DATA MANAGEMENT (3 credits) - Prerequisites: Appropriate background is one semester of applied statistics or equivalent. Students learn data organization and structures, design of statistical databases, statistical software analysis, importing and exporting of data between software, and missing data analysis.

589 TOPICS IN STATISTICS (1-3 credits; may be repeated for a total of six credits) - Prerequisite: permission. Selected topics in advanced statistics, including quality control, reliability, sampling techniques, decision theory, advanced inference, stochastic processes and others.

591 WORKSHOP IN STATISTICS (1-3 credits; may be repeated with change of topic - Group studies of special topics in statistics. May not be used to meet undergraduate or graduate major requirements in mathematics and statistics. May be used for elective credit only.

595 STATISTICAL CONSULTING (1-3 credits) - Prerequisite: 580 or permission. Students will be assigned to work with an instructor on current projects in the Center for Statistical Consulting. May be repeated for a total of 4 credits; however, only 2 credits will count toward major requirements. Does not count for elective credit for math science department majors.

650 ADVANCED PROBABILITY AND STOCHASTIC PROCESSES (3 credits) - Prerequisite: 651. Random walk, distributions, unlimited sequence of trials, laws of large numbers, convolutions, branching processes, renewal theory, Markov chains, time-dependent stochastic processes.

651 PROBABILITY AND STATISTICS (4 credits) - Prerequisite: Appropriate background is three semesters of calculus or equivalent. Probability, random variables, moments and generating functions, random vectors, special distributions, limit theorems, sampling, point estimation, hypothesis testing, confidence estimation.

652 ADVANCED MATHEMATICAL STATISTICS (3 credits) - Prerequisite: 651. Convergence of random variables, the Central Limit Theorem; theory of estimation; theory of hypothesis testing; the multivariate normal density; introduction to linear models; Bayesian statistics.

655 LINEAR MODELS (3 credits) - Prerequisites: Appropriate background is linear algebra or 651 or equivalent. General linear model in matrix notation, general linear hypothesis, regression models, experimental design models, analysis of variance and covariance, variance components.

660 ADVANCED STATISTICAL METHODS (4 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Theory and applications of the techniques of regression and multifactor analysis of variance.

661 STATISTICS FOR THE LIFE SCIENCES (3 credits) - Prerequisite: college level algebra or equivalent. Data description and presentation, probability applications in the life sciences (including sensitivity, specificity, relative risk), principles and application of statistical inference, ANOVA, correlation and regression.

663 EXPERIMENTAL DESIGN (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Selected topics in experimental design including random and fixed effects, nested designs, split plot designs, confounding, fractional factorials, Latin squares, and analysis of covariance.

664 STATISTICS FOR THE HEALTH SCIENCES (4 credits; may not be used to meet degree requirements for mathematical sciences majors). Prerequisite: college-level algebra or equivalent. Descriptive statistics, probability and probability distribution, tests of hypotheses and confidence intervals, nonparametric statistics, regression and correlation.

665 REGRESSION (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Correlation, simple and multiple linear regression: least squares, matrix notation, model building and checking, estimation, hypothesis testing, outliers, influence, multicollinearity, transformations, categorical regressors; logistic regression.

666 NONPARAMETRIC STATISTICS-METHODS (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Theory and practice using techniques requiring less restrictive assumptions. Nonparametric analogues to t- and F-tests, ANOVA, regression and correlation. Computer applications.

667 FACTOR ANALYSIS (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Theory and techniques for identifying variables through use of principal components and factor analysis. Identification of groups using cluster analysis. Computer applications.

668 MULTIVARIATE STATISTICAL METHODS (3 credits) - Prerequisite: Appropriate background is two semesters of applied statistics or equivalent. Multivariate techniques including distance concept, Hotelling's T², multivariate ANOVA, regression and correlation, linear contrasts, factorial experiments, nested and repeat measure designs, Bonferroni X² tests, linear discrimination analysis, canonical correlations, application.

670 BIOSTATISTICS (3 credits) - Prerequisite: Appropriate background is one semester of applied statistics or equivalent. Statistical issues and methods for biological, medical and health sciences including: clinical trials, sample size, power, log-linear models, survival analysis, and bioassay. Computer applications.

675 RESPONSE SURFACE METHODOLOGY (3 credits) - Prerequisite: Appropriate background is two semesters of applied statistics or equivalent. First and second order response designs, efficient experimental plans, methods for the analysis, and optimization of response functions.

689 ADVANCED TOPICS IN STATISTICS (1-3 credits; may be repeated for a total of six credits) - Prerequisite: 651. Selected topics in statistics including concepts in biometry, order statistics, advanced inference, sequential analysis, stochastic processes, reliability theory, Bayesian statistics and regression.

692 STATISTICS MASTERS PAPER (1-3 credits; may be repeated) - Prerequisite: permission of advisor. Seminar-type discussion on topics in statistics leading to supervised research project. No more than 2 credits apply to major requirements.

695 PRACTICUM IN STATISTICS AND MATHEMATICS (1-3 credits) - Prerequisite: graduate teaching assistant or permission. Training and experience in college teaching of statistics. May not be used to meet degree requirements. Credit/noncredit.

697 INDIVIDUAL READING (1-2 credits; may be repeated for a total of four credits) - Prerequisites: graduate standing and permission. Directed studies in statistics under guidance of selected faculty member.

698 MASTER’S RESEARCH (1-6 credits; may be repeated) - Prerequisite: permission of advisor. Research in suitable topics in statistics culminating in a research paper. No more than 2 credits applicable to major requirements.

699 MASTER’S THESIS (2 credits; may be repeated for a total of 4 credits) - Prerequisite: Permission. Properly qualified candidates for master’s degree may obtain 2-4 credits for research experience which culminates in presentation of faculty-supervised thesis.