Anna University Statistics For Management Book Pdf
Jacqualine Henington
Dr. Coffey is a Professor of Biostatistics and Director of the Clinical Trials Statistical and Data Management Center (CTSDMC) in the University of Iowa College of Public Health. He received his Ph.D. in biostatistics from the University of North Carolina at Chapel Hill
Dr. Bayman is an Associate Professor of Biostatisics, with a secondary appointment in the Department of Anesthesia. She has over 12 years of experience providing statistical design expertise to multi-center clinical trials,
Dixie J. Ecklund, RN, MSN, MBA is the Director of Operations for the University of Iowa Clinical Trials Statistical & Data Management Center (CTSDMC) and manages the day-to-day activities of the Center.
CTSDMC biostatisticians prepare and validate study reports, as well as interim and final analyses for CTSDMC projects. CTSDMC also supports the work of graduate students in the Department of Biostatistics.
The CTSDMC provides full-range data management support, including developing case report forms, specifications and testing plans, validating the data systems, managing the query system, and assisting in end-user training and technical support of the database.
The IT/Development Group is responsible for installation and maintenance of all hardware and software systems. This group is responsible for overseeing the design and implementation of all data systems, and ensuring that they conform to standards set by the FDA.
The Protocol Coordination and Monitoring group is responsible for developing and executing all monitoring plans in each clinical study. They provide on-site, remote and risk-based monitoring, study site support including EDC training, adverse event reporting and the development of training materials.
The Research Scientist Group provides various specialized scientific research findings by analyzing study data, performing research simulations and theoretical investigations for numerous CTSDMC studies.
The School of Accounting, Finance, Economics and Decision Sciences offers courses leading to the Master of Science degree in Applied Statistics and Decision Analytics. The MS 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 33 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 Python, SAS, Tableau, and 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 Applied Statistics and Decision Analytics degree program at Western Illinois University has been designated by the U.S. Immigration and Customs Enforcement agency within the Department of Homeland Security as a STEM-eligible degree program (CIP code 27.0501). The STEM designation allows eligible graduates on student visas access to an Optional Practical Training (OPT) extension, up to 36 months, as compared to 12 months for non-STEM degrees. As an international student, the longer work authorization term may help you gain additional real-world skills and experience in the U.S.
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 depending on remaining capacity in 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.
*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.
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 a 19 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.
445G (cross-listed with FIN 445G) Financial Modeling and Statement Analysis. (3) Students will identify problems, analyze results, and make decisions regarding the impact on financial statements through development of models in electronic spreadsheets. Financial statements, capital budgets, risk, capital structures, takeovers, and other financial topics will be analyzed. Prerequisite: ACCT 341 or FIN 331 or permission of the instructor.
481G Database Programming. (3) Introduction to practical aspects of querying relational databases (using SQL). Creating applications written in high-level, general-purpose programming languages (Python) for interacting with databases. Necessary programming fundamentals, principles of database querying, developing applications that work with databases. Prerequisites: STAT 171 or permission of the instructor.
540 Computer Simulation. (3) Statistical techniques used in computer simulations. Construction and verification of simulation models. Programming projects. Prerequisites: One statistics course and familiarity with two programming languages.
421G Data Visualization for Decision Making. (3) This course provides introduction to the process and methods of visualization information for the purpose of communicating actionable findings in a decision-making context. Hands-on experience with software for sourcing, organizing, analyzing, comprehending, reducing, and visualizing data. Not open to students who have already completed DS 521. Prerequisites: STAT 171 or DS 200 or equivalent; or permission of instructor.
423G Management Science Techniques & Business Analytics. (3) An introduction to management science/operations research techniques. Students are introduced to the theory and applications of linear, integer, goal, and dynamic programming models; transportation, assignment, network and inventory models; PERT/CPM, capital budgeting, and decision theory. Not open to students who have already completed DS 523.Prerequisites: STAT 171 or equivalent.
435G Applied Data Mining for Business Decision-Making. (3) 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. Prerequisite: DS 303 or STAT 276 or permission of instructor.
480G Predictive Analytics. (3) A survey of topics in predictive analytics methods and techniques essential for business analytics. Topics include time series regression, logistic regression, neural networks, decision trees, ensemble models, and simulation models for understanding the effect of uncertainty. Not open to students who have already completed DS 580. Prerequisites: DS 490 or CS 114, and 6 s.h. of either STAT or DS coursework; or permission of the instructor.
485G Big Data for Business Decision Making. (3) This course provides an introduction to big data analytics tools and methods for business applications. Topics include exploration, classification, dimension reduction, structured and unstructured data. Statistical software will be used to analyze business data. Prerequisites: STAT 171, DS 200, and DS 303 or equivalent; and CS 114 or DS 490 or equivalent; or permission of the instructor.
489G Seminar in Contextual Business Analytics. (3) An industry, case study, focused course that explores topics relevant to applying business analytics models and theories to current corporate projects. Exact topics will change based on instructor expertise and market trends. Prerequisites: DS 490 or CS 114, and 6 s.h .of additional DS coursework; or permission of the instructor.
490G Statistical Software for Data Management and Decision Making. (3, repeatable to 6 for different titles) 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. Prerequisites: STAT 171 or equivalent, and DS 303 or PSY 223 or SOC 324 or POLS 284 or equivalent; or permission of the instructor.
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