Applied Statistics and Decision Analytics - New Program 2016-2017
The Department of Economics and Decision Sciences offers courses leading to the Master of Science degree in Applied Statistics and Decision Analytics. Further information concerning the program and areas of specialization may be obtained from the department chairperson. The Master of Science degree is not reviewed for accreditation by AACSB International.
The Master of Science in Applied Statistics and Decision Analytics is a multidisciplinary graduate degree program with a unique focus on applied statistics and decision analytics. This program is intended for graduates from undergraduate programs in the quantitative and biological sciences, mathematics, sociology, psychology, business, computer sciences, physics, engineering, and education, as well as working professionals desiring to sharpen their data-analysis and analytical skills and learn advanced statistical methods. The 36-semester-hour curriculum provides students with a firm foundation of statistical analysis and modeling commonly used in many fields, including education, science, technology, health care, government, business, or social science research. The graduates of the program will be trained on industry-standard software packages, such as SAS and/or R, and gain modern analytical skills that are sought after in many fields, particularly in the areas of business and decision analytics or data analytics. The program is designed to include 15 semester hours (s.h.) of core courses, 6 s.h. of directed electives, and 15 s.h. from one of the following: a thesis option, an internship option, or an all coursework option.
Building on the recommendations of the American Statistical Association (ASA)’s professional panel of experts (see, Amstat News, February 2013, http://magazine.amstat.org): “Preparing Master’s Statistics Students for Success: A Perspective from Recent Graduates and Employers,” graduates of our master of science in applied statistics and decision analytics degree program will be able to:
- apply advanced statistical methodologies, including a) descriptive statistics and graphical displays; b) probability models for uncertainty, stochastic processes, and distribution theory; c) hypothesis testing and confidence intervals; d) ANOVA and regression models (including linear, and multiple linear) and analysis of residuals from models and trends; and e) predictive modeling, forecasting, design of experiments, and stochastic models in applied statistics and decision analytics;
- derive and understand basic theory underlying these methodologies;
- formulate and model practical problems for solutions using these methodologies;
- produce relevant computer output using necessary and sufficient programming skills and standard statistical software (e.g., SAS, R, STATA, etc.) and interpret the results appropriately;
- communicate statistical concepts and analytical results clearly and appropriately to others;
- understand theory, concepts, and terminology at a level that supports lifelong learning of related methodologies; and
- identify areas where ethical issues may arise in statistics.
The need for skilled data professionals is real and growing. According to a study by the McKinsey Global Institute, United States could face a shortage of as many as 190,000 workers with “deep analytical skills” by 2018. This program seeks to combine the course work of statistical decision making and analytic tools to meet the demand for skilled workers in the U.S. and Illinois job markets. With three Fortune 100 companies in the region—John Deere, Caterpillar, and State Farm—the degree program is designed to address strong regional needs and/or a shortage of graduates in the fields of applied statistics and decision analytics. Due to the shortage of skilled data and business analysts, the market demand is strong for graduates in this field. Companies hiring include Caterpillar, John Deere, Hewlett-Packard, Honeywell, Northrop Grumman, Boeing, American Medical Association, Chicago Board of Trade, U.S. Treasury, U.S. Comptroller of the Currency, Tennessee Department of Commerce, Principal Financial Group, Bank of America, Merrill Lynch, Exxon, Illinois Power, Newsweek, and WalMart.
For admission to the Master of Science in Applied statistics and Decision Analytics degree program, students should have undergraduate preparation in a relevant area, such as, mathematics, statistics, economics, quantitative or biological sciences, sociology, psychology, business, computer sciences, physics, engineering, education. Applicants for admission to the Master of Science degree program in Applied Statistics and Decision Analytics must satisfy the standards for admission to School of Graduate Studies at Western Illinois University.
Application for admission to the School of Graduate Studies must be made online at www.wiu.edu/grad/apply. Applicants must hold a bachelor’s degree from an institution that is accredited by the appropriate U.S. Department of Education regional accrediting agency. Applicants are required to provide proof of such degree by submitting an official degree transcript for each college or university previously attended directly to the School of Graduate Studies. Transcripts on file in the Office of the Registrar at WIU will be obtained by Graduate School personnel.
Applicants for admission to the School of Graduate Studies must have either a cumulative grade point average of at least 2.75 (based on all hours attempted at all institutions attended) for undergraduate work, OR a 3.0 or higher grade point average for the last two years (60 s.h.) of undergraduate work.
While the GRE is not required, applicants, however, are encouraged to take the GRE and submit the GRE results to strengthen their respective applications for admission in the program.
Admission to any graduate degree program at WIU is contingent upon successful completion of undergraduate coursework specified as a prerequisite. If an applicant is deficient in any or all of the minimum requirements for admission into program, such an applicant may be provisionally admitted into the program subject to the completion of all deficiencies before taking any required courses within the program. The applicants will be duly notified what deficiency courses they need to take at Western Illinois University before they will be allowed to enroll in any of the required courses in the program.
The set of deficiency courses that the applicants may be asked to complete, immediately upon being provisionally admitted into the program and depending on what the applicant may be deficient in, will be Calculus with Analytical Geometry I and II (Math 133 and Math 134) or equivalents; Linear Algebra (Math 311) or equivalent; and Introduction to Probability & Statistics/Business Statistics for Managerial Decision Making (Stat 276/DS 503) or equivalent. Students deficient in the minimum course requirements will be required to take one or more courses to remove these deficiencies prior to enrolling in the courses that are part of the program core requirements. Applicants for graduate assistantship are also required to provide at least three letters of reference from individuals who can provide meaningful comments on the student’s professional and/or academic background and a statement of interest (not to exceed two pages in length).
Students whose native language is other than English must demonstrate written and spoken English language proficiency. Evaluation of English language proficiency will be based on the student’s scores on the Test of English as a Foreign Language (TOEFL®). Students must meet institutionally mandated minimum TOEFL® scores as established by the WIU Center for International Studies.
Applicants are also required to provide at least three letters of reference from individuals who can provide meaningful comments on the student’s professional and/or academic background and a statement of interest (not to exceed two pages in length).
I. Core Courses: 15 s.h.
STAT 471G Introduction to Mathematical Statistics I (3 s.h.)
STAT 478G Analysis of Variance (3 s.h.)
STAT 553 Applied Statistical Methods (3 s.h.)
DS 435G Applied Data Mining for Business Decision Making (3 s.h.)
DS 490G Statistical Software for Data Management and Decision Making (3 s.h.)
II. Directed Electives: 6 s.h.
A. Modeling and Prediction (Choose one of the following):
DS 533 Applied Business Forecasting and Planning (3 s.h.)
DS 580 Business Analytics and Forecasting (3 s.h.)
ECON 506 Econometrics I (3 s.h.)
STAT 474G Regression and Correlation Analysis (3 s.h.)
PSY 551 Structural Equation Modeling for the Behavioral Sciences (3 s.h.)
B. Sampling and Experimental Design (Choose one of the following):
BIOL 501 Biometrics (3 s.h.)
ECON 507 Econometrics II (3 s.h.)
SOC 530 Statistical Methods (3 s.h.)
PSY 501 Advanced Psychological Statistics (4 s.h.)
STAT 574 Linear Models and Experimental Design (3 s.h.)
III. Select one of the following Exit Options: 15 s.h.
A. Thesis Option
Thesis (6 s.h.)
Electives* (9 s.h.)
B. Internship Option
Internship (3–9 s.h.)
Electives* (6–12 s.h.)
C. Coursework Option
Electives* (15 s.h.)
* Upon approval from the program graduate advisor, students may select elective courses listed above under I and II (excluding those courses that are otherwise used to fulfill the requirements under I and II) or from additional program-specific and related electives from Computer Science, Decision Sciences, Economics, Mathematics, Statistics, or other 500-level graduate courses in Research/Quantitative Methods (Techniques), Applied Business Research, etc., from Law Enforcement and Justice Administration, Management, Marketing, Sociology, Psychology, etc.
TOTAL PROGRAM: 36 s.h.
The capstone courses are fundamental in providing the knowledge and tools necessary in formulating statistical hypotheses and analyzing final results. Students must complete 36 semester hours and may follow either a Thesis or an internship or a Non‑Thesis Option. Consultation with and approval of the program graduate advisor concerning course selection is required to insure completion of all requirements. Students wishing to take a readings and/or internship course must receive approval from the economics and decision sciences department prior to registration.
Students may select courses outside of the economics courses which will assist them in achieving their career goals. A maximum of nine hours of related courses from other disciplines is allowed with permission of the graduate committee chairperson. The student may petition for an additional three hours of related course work outside of the economics courses. All special permissions or petitions must be approved prior to registration. Transfer and extension credit will be accepted in accordance with current School of Graduate Studies policy.
While all graduate students must complete the required core courses, it is possible to elect courses that will enhance specific career objectives. For further information on elective concentrations consult the program graduate advisor.
The Department of Economics and Decision Sciences also offers an 18 s.h. post-baccalaureate certificate (PBC) in Business Analytics. The Business Analytics PBC offers the technical skills of data mining, statistical modeling, and forecasting for data-driven decision-making and for solving the analytical problems of the contemporary business world. For program details, go to the post-baccalaureate certificates page.
Chairperson: Tej Kaul
Graduate Committee Chairperson: Steven Rock
Graduate Advisor: Farideh Dehkordi-Vakil
- Farideh Dehkordi-Vakil, Ph.D., University of Iowa
- Tej K. Kaul, Ph.D., Birla Institute of Technology and Science
- Kasing Man, Ph.D., University of Chicago
- Alla Melkumian, Ph.D., West Virginia University
- Steven M Rock, Ph.D., Northwestern University
- Jessica Lin, Ph.D., Binghamton University
- William J. Polley, Ph.D., University of Iowa
- Thomas R. Sadler, Ph.D., University of Tennessee-Knoxville
- Shane Sanders, Ph.D., Kansas State University
- Bhavneet Walia, Ph.D., Kansas State University
Associate Graduate Faculty
- Anna Valeva, Ph.D., University of California-Santa Barbara
- Tara Westerhold, Ph.D., University of South Carolina
- Shankar Ghimire, Ph.D., Western Michigan University
- Keva Hibbert, Ph.D., Binghamton University
- Cumulative: 2.75
- Last 2 years: 3.0
Interesting Facts: Fall 2016
- Currently enrolled: 5
- International: 3
- Minority: 1
- Male: 3
- Female: 2
- Students with Assistantships: 2
Department Contact Information:
Stipes Hall 430