This content is password protected. To view it please enter your password below:

Request Information

The 100% online Marian University Undergraduate Certificate in Data Analytics focuses on the implementation, analysis, and interpretation of insights from data of various sources. Students will experience coursework in programming, database management, and mathematics. These components are based on industry identified competencies recommended in the field by employers who hire data analysts. The skills and knowledge required for this comprehensive program cut across core disciplines of information systems, computer science, mathematics, and statistics.

Students earn a Certificate in Data Analytics by completing 13 bachelor-level credits:

(AGS students only)   A study of topics that include descriptive statistics and data analysis; elementary probability; binomial, hypergeometric and normal probability models; the central limit theorem; confidence intervals; elementary hypothesis testing; linear regression; and correlation. A major goal of this course is the application of these topics to problems arising from the natural sciences, the social sciences, the health industry and the business environment.

Examination of fundamental concepts needed to understand data mining, visualization and descriptive statistics to assist in business decision making. Learners will review data summarization and application of analytics to advance comprehension for various business environments.

Prerequisites:

MAT 001 Basic Algebra, Appropriate math placement test score or MAT 001 with grade of C or higher

An interdisciplinary introduction to the basic principles of data analysis with an emphasis on application. Students are expected to apply these principles to data analysis in their respective areas of study. The applied focus is on the computerized application of summary statistics, one/two/multi-sample tests, linear models, association tests, randomness/normality tests, time series comparison, quality control charts and probability distributions as used across a variety of community and organizational settings. Other techniques may be added as appropriate for specific disciplines.

or

Prerequisites:

An interdisciplinary introduction to the basic principles of data analysis with an emphasis on application. Students are expected to apply these principles to data analysis in their respective areas of study. The applied focus is on the computerized application of summary statistics, one/two/multi-sample tests, linear models, association tests, randomness/normality tests, time series comparison, quality control charts and probability distributions as used across a variety of community and organizational settings. Other techniques may be added as appropriate for specific disciplines.

This course introduces information technology systems that support organizational decision-making and problem solving. The course surveys the technical and organizational issues involved in the use and design of information systems and how the application of IT can enable an organization to improve quality, timeliness, and competitive advantage.

Prerequisites:

( also FIN 403) This course deals with computer applications in quantitative management decision making at an advanced level. Students will utilize a variety of research tools to locate, analyze and evaluate information. It will investigate the use and application of computer technologies within organizations such as management support systems, decision support systems and executive information systems. Hands on application of front-end software, such as Microsoft Office, will be used to conceptualize, analyze, and develop technological solutions to practical business situations.

Data, Research, and Ethics: Students will combine research design and data from more than one perspective; develop a methodology; and discuss relevant solutions, the associated limitations, and implications in a manner that considers multiple contextual factors. They will recognize ethical issues for data and research when presented in a complex, multilayered context and apply cross-cutting ethical perspectives among those issues.

Critical Thinking and Problem Solving: Learners will systematically and methodically analyze their own and others’ assumptions/viewpoints to carefully place evidence and perspectives in priority order to inform evaluation and articulate the limitations.

Integrated Communication: Individuals will organize and synthesize information by choosing formats in verbal, written, and visual language that enhance meaning.

Technological Dexterity: Students will access a variety of information sources with well-designed strategies using multiple criteria. They will determine how to assess key concepts using observable measures to answer questions, and execute procedures for accurate, reliable, and valid data collection, storage, security, transfer, and export.

Quantitative Reasoning: Those in the program will understand and articulate the mathematical and statistical assumptions and potential consequences underpinning the sources of information, data, and analyses.

Marian University is accredited by the Higher Learning Commission.

Linda Krueger, M.S.
Assistant Professor
920.923.8739
lkkrueger64@marianuniversity.edu

Laramie Paxton, Ph.D.
Assistant Professor
920.923.7647
lspaxton43@marianuniversity.edu

Marian University graduates apply the knowledge they gain in class to solving real-world problems. For more information, please contact:

Office of Admission
920.923.7650
admission@marianuniversity.edu

Apply Now