MASTER OF SCIENCE

Analytics

This 36-semester hour program prepares the student by providing depth in analytics during the first year and focused functional study during the second year that can be applied to any discipline or any interdisciplinary area.  Data analysts are forging new relationships in virtually every discipline: business, healthcare, geology, mathematics and statistics, biology, chemistry, computer science, information systems and technology, engineering, psychology, behavioral science, operations research and more, in addition to potential interactions between these disciplines, using role-based interaction with information and analytics to enable highly- collaborative, data-driven organizations  The graduate of this program enters the workforce prepared for the complex, information-intensive world.

The core Analytics courses are described below. For a complete list of all course descriptions please refer to the Harrisburg University course catalog.


ANLY 500 Analytics I: Principles and Applications (3 semester hours)
Prerequisites: MATH 220 and 280

Corequisites: MATH 510 or demonstrated competency in mathematics, statistics, and applied statistics at the discretion of the advisor.

Description: This course covers the core concepts and applications of analytics in different domains.  The student is introduced to the main concepts and tools of analytics (e.g., data querying and reporting, data access and management, data cleaning, statistical programming, data mining introduction, relational databases, and statistical analysis of databases).  The student is also introduced to the emerging topics in data sciences such as Big Data, Smart (Semantic) Data, data modeling, and data visualization.  The student then applies the principles of analytics/data sciences to different domains such as health, education, public safety, public welfare, transportation, and other public and private sectors.  The student is then encouraged to apply the concepts to a domain of interest.

 

ANLY 502 Analytical Methods I (3 semester hours)
Prerequisites: None

Description: This course reviews the fundamental mathematics required to be successful in the analytics program.  It is designed to strengthen the mathematical abilities while addressing the requirements for coding/scripting.  It presents the mathematical topics as coding/scripting problems.  This is intended to further strengthen the ability to develop the subroutines/codes/scripts that are also necessary in an analytics career.

 

ANLY 506 Exploratory Data Analysis (3 semester hours)
Prerequisites: None

Description: Exploratory data analysis plays a crucial role in the initial stages of analytics.  It comprises the pre-processing, cleaning, and preliminary examination of data.  This course provides instruction in all aspects of exploratory data analysis.  It reviews a wide variety of tools and techniques for pre-processing and cleaning data, including big data.  It provides the student with practice in evaluating and plotting/graphing data to evaluate the content and integrity of a data set.

 

ANLY 510 Analytics II: Principles and Applications (3 semester hours)
Prerequisites: ANLY 500

Description: This course provides a comprehensive background for the student who wants to engage in advanced analytics projects in the public and private sectors.  The student is exposed to descriptive, predictive as well as prescriptive analytics techniques.  The course begins with a review of the descriptive analytics concepts (i.e., sampling and statistical inferences) ANLY 500 that are used to discover and understand correlations.  It then concentrates on predictive analytics techniques such as regression, forecasting, and simulations that can be used to predict future events based on past data.  The course concludes with the perceptive analytics techniques that attempt to find the “best” solutions by using linear and non-linear optimization techniques and statistical decision models.  The student is strongly encouraged to apply the concepts to domains of interest.

 

ANLY 512 Data Visualization (3 semester hours)
Prerequisites: ANLY 500

Description: The visualization and communication of data is a core competency of analytics.  This course takes advantage of the rapidly evolving tools and methods used to visualize and communicate data.  Key design principles are used to reinforce skills in visual and graphical representation.

 

ANLY 545 Analytical Methods II (3 semester hours)
Prerequisites: ANLY 502

Corequisites: MATH 510 or demonstrated competency in mathematics, statistics, and applied statistics at the discretion of the advisor.

Description: This course provides student with exposure to an expanded range of analytical methods.  This includes additional functions, e.g. the logit function, additional distributions, e.g. Poisson distribution, and additional analysis techniques, e.g. those included in the study of discrete structures such as combinatorics. Particular attention is paid to analytics relevant to disciplines in the social sciences.  Also included are survey design, development and (survey data) analysis.