Economics and Decision Sciences

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Master of Science Applied Statistics and Decision Analytics

The Illinois Board of Higher Education (IBHE) approved a the Master of Science in Applied Statistics and Decision Analytics, at Western Illinois University, beginning Spring 2016.

The Master of Science (M.S.) in Applied Statistics and Decision Analytics is a multidisciplinary graduate degree program with a unique focus. The M.S. degree in Applied Statistics and Decision Analytics is a 36-semester hour (sh) curriculum designed to provide 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. Students in this program will be trained on industry-standard software packages and gain modern analytical skills. The need for skilled data professionals is growing. According to a study by the McKinsey Global Institute, the 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.

Learning Objectives

Building on the recommendations of the American Statistical Association (ASA)’s professional panel of experts, graduates of the M.S. in Applied Statistics and Decision Analytics program will be able to:

  1. Apply advanced statistical methodologies; derive and understand basic theory underlying these methodologies; and formulate and model practical problems for solutions using these methodologies
  2. 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
  3. Communicate statistical concepts and analytical results clearly and appropriately to others
  4. Identify areas where ethical issues may arise in statistics

Why WIU?

  • Large enough to offer a wide variety of courses, yet small enough to provide individual attention
  • Faculty members who are genuinely interested in students’ intellectual development
  • Advising tailored to students’ personal needs and educational goals
  • Opportunities for interacting with students from other cultures and countries

Faculty Expertise

The faculty members in the WIU Department of Economics and Decision Sciences take an active and sincere interest in student success. Our faculty are also active in research, so students learn state-of-the-art skills and techniques. All faculty teaching graduate courses have PhDs in economics or statistics.

Career Opportunities

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

  • American Medical Association
  • Bank of America
  • Boeing
  • Caterpillar
  • Chicago Board of Trade
  • Exxon
  • Hewlett-Packard
  • Honeywell
  • Illinois Power
  • John Deere
  • Merrill Lynch
  • Newsweek
  • Northrop Grumman
  • Principal Financial Group
  • Tennessee Department of Commerce
  • U.S. Comptroller of the Currency
  • U.S. Treasury
  • Walmart
Master's program graduate in cap and gown

Please refer to the graduate catalog for detailed program information and course requirements.

Core Courses

STAT 471G Introduction to Mathematical Statistics

The mathematical foundations of probability and statistics, principles of probability, sampling, distributions, moments, and hypothesis testing.

STAT 478G Analysis of Variance

A study of analysis of variance and covariance with applications. Includes experimental design.

STAT 553 Applied Statistical Methods

Introduction to probability and statistics with a significant lean toward applications. Topics include probability, probability distributions, Central Limit Theorem, sampling distributions (t, F, Chi-Square), parameter estimation, hypothesis testing, nonparametric statistics, ANOVA, and linear regression.

DS 435G Applied Data Mining for Business Decision Making

This course provides an introduction to data mining methods for business applications. Students will learn the basics of data selection, preparation, statistical modeling, and analysis aimed at the identification of knowledge fulfilling organizational objectives.

DS 490G Statistical Software for Data Management and Decision Making

This course provides students with the basic concepts of statistical computing. Students will gain experience with statistical software packages, such as SAS or SPSS, and their applications. Methods of data preparation and validation, analysis, and reporting will be covered.

Electives Courses: Modeling and Prediciton (choose one)

DS 533 — Applied Business Forecasting and Planning

A survey of the basic forecasting methods and techniques essential for modern managers. Topics include moving average and decomposition techniques, ARIMA processes, regression techniques, and technological methods such as Delphi and S-curves.

DS 580 — Business Analytics and Forecasting

This course introduces analytical models and tools used for continuous iterative exploration and investigation of past business performance to gain insight and drive decision. Predictive modeling, forecasting, and design of experiments will be covered.

ECON 506 — Econometrics I

Elements of the theory and practice of econometrics: including univariate and multivariate single equation models, statistical problems such as multicollinearity, special techniques and applications, and an introduction to simultaneous equations models. Students will complete a project involving hypothesis formulation, data collection, analysis using statistical software, and written presentation of results.

STAT 474G — Regression and Correlation Analysis

Least squares theory; correlation theory; simple, multiple, and stepwise regression; computer assisted model building; and applied problems.

PSY 551 — Structural Equation Modeling for the Behavioral Sciences

Structural equation modeling (SEM) and related analytical approaches employed in the behavioral sciences will be explored, with an emphasis on interpretation. Multiple regression and factor analysis will be reviewed. Hands-on training with contemporary SEM software will be provided.

Electives Courses: Sampling and Experimental Design (choose one)

BIOL 501 — Biometrics

Basic methods of experimental design and evaluation of biological data.

ECON 507 — Econometrics II

Advanced econometric estimation to include estimating micro and macroeconomic functions through simultaneous equation systems, dummy dependent variable models; and multivariate analysis. Class culminates in an independent research project.

SOC 530 — Statistical Methods

Modern statistical techniques and methods of data analysis in the social sciences. Data reporting, random variation and sampling procedures, interviewing, secondary data sources, the search of unobtrusive measurements, and techniques of data processing.

PSY 501 — Advanced Psychological Statistics

A consideration of advanced statistical methods and experimental designs which are applicable to psychological research. Particular attention is given to correlation and analysis of variance.

STAT 574 — Linear Models and Experimental Design

General linear models, Gauss Markov Theorem, experimental design model confounding, and types of experimental designs and their analysis.

Exit Options

  • Thesis and Electives
  • Internship and Electives
  • Corsework

Admission Requirements

Applicants must hold a bachelor’s degree from an institution that is accredited by the appropriate U.S. Department of Education’s regional accrediting agency. Application for admission to the WIU School of Graduate Studies must be made online at wiu.edu/grad/apply. 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 sh) of undergraduate work. While the GRE is not required, applicants are encouraged to take the GRE and submit the results to strengthen their respective applications for admission to 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 the program, the 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 notified what deficiency courses they need to take at Western before they will be allowed to enroll in any of the required courses in the program. The set of deficiency courses 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 assistantships are also required to provide at least three letters of reference from individuals who can provide meaningful comments on a student’s professional and/or academic background and a statement of interest (not to exceed two pages in length).

Degree Requirements

I Core Courses: Fifteen semester hours (15 sh) of core courses will be chosen from the following: Introduction to Mathematical Statistics I (STAT 471G), Analysis of Variance (STAT 478G), Applied Statistical Methods (STAT 533), Applied Data Mining for Business Decision Making (DS 435G), and Statistical Software for Data Management and Decision Making (DS 490G).

II Directed Electives: Six semester hours (6 sh), one three-hour course from each category A and B:

  • Modeling and Prediction (Choose one of the following): Applied Business Forecasting and Planning (DS 533), Business Analytics and Forecasting (DS 580), Econometrics I (ECON 506), Regression and Correlation Analysis (STAT 474G), or Structural Equation Modeling for the Behavioral Sciences (PSY 551).
  • Sampling and Experimental Design (Choose one of the following): Biometrics (BIOL 501), Econometrics II (ECON 507), Statistical Methods (SOC 530), Linear Models and Experimental Design (STAT 574), or Advanced Psychological Statistics (PSY 501).

III. Capstone: There are three options for completing the remaining 15 sh: (1) Thesis, (2) Internship, and (3) Coursework options. The thesis option consists of 9 sh of elective* courses plus 6 sh of Thesis. The Internship option consists of 3-9 sh of Internship and 6-12 sh of elective* courses. The coursework option consists of 15 sh of elective* courses.

*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.

Contact

Economics and Decision Sciences

Dr. Tej Kaul, Chairperson
Email: T-Kaul@wiu.edu
Location: Stipes Hall 430
1 University Circle
Macomb, IL 61455-1390
Phone: (309) 298-1153
Fax: (309) 298-1020

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Economics and Decision Sciences Graduate Program Advisor

Farideh Dehkordi-Vakil
Email: F-Dehkordi@wiu.edu
Location: Stipes Hall 430K
Phone: (309) 298-2234

College of Business & Technology (CBT)

Dr. John A. Elfrink, Interim Dean
Email: JA-Elfrink@wiu.edu
CBT Email: cbt@wiu.edu
Location: Stipes Hall 101
1 University Circle
Macomb, IL 61455-1390
Phone: (309) 298-2442
Fax: (309) 298-1039

CBT Website

CBT Directory

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