Introduction

The Statistics and Predictive Analytics degree at RMU prepares students for the growing need of analyzing large data sets using advanced statistical techniques to make large scale decisions. Students with a love for mathematics with a desire to solve complex problems as a respected professionals should give serious consideration to the opportunities this degree provides.  Individuals with the ability to perform detailed statistical analysis are often referred to as Statisticians while those who can combine these skills with an understanding of processing, extracting, and organizing large amounts data in a meaningful way are known as Data Scientists.  This degree provides the tools to reach the role of the latter.  Data Scientists and Statisticians are currently the two highest rated careers for 2016 according to CareerCast.com.

Predictive Analytics has exploded into every major industry by providing tools to extract, efficiently organize, and analyze useful data to improve decision making processes.  The RMU Statistics and Predictive Analytics degree prepares students for this exciting field by providing them with a strong skillset in mathematics, statistics, and database management while giving them the opportunity to work with large data sets.  In 2012, the Harvard Business Review titled an article "Data Scientist: The Sexiest Job of the 21st Century" (HBR).

The degree provides not only a strong background in statistics but also gives students the opportunities to work directly with large data sets  This experience also assists in determining what statistical techniques and software are appropriate to solve problems.  A large focus is given to provide students with exposure to working with data to assist them in developing an intuition towards data analysis.  The curriculum integrates the foundations of statistical and data analysis with communications skills. Our mission is to produce enlightened graduates with cultural and civic awareness, as well as the technical proficiency and analytical ability to be productive professionals.

The major is highly interdisciplinary in content.  Students are required to take courses in general mathematics, statistics, database management, business, finance, programming, science, and communications.

Applicants should have a very high aptitude and solid background in mathematics. An ACT mathematics sub-score of at least 27 or an SAT mathematics sub-score of at least 640 is required for unconditional entrance into the program. The admissions review committee will accept students with lower sub-scores on a probationary basis.

What is Predictive Analytics?

Recently, technology has made it possible for companies in many industries to gather and store vast quantities of information and data related to many variables of interest.  Predictive Analytics makes use of these large data sets to help draw conclusions about recent activity, to learn about the relationships between variables, to cluster similar data points into groups, or to make predictions about the future.  This is generally done using sophisticated statistical methodologies and algorithms to classify data points, determine if patterns exist, and gain insights and understanding about the various variables in the data set.  Once this is done, companies can apply these insights to improve upon their procedures and decision-making processes in various areas of their business.  

Examples of Applications in Statistics and Predictive Analytics

Analytics have become extremely popular in a wide range of fields:

  • Organizations in various sports use predictive analytics to evaluate a playera??s value or optimize their performance.
  • Surgeons use devices with sensors that analyze large amounts of data during a medical procedure to make real-time decisions.
  • Pharmaceutical companies use revolutionary methods to analyze data in the process of developing and testing new drugs. 
  • Retail stores analyze data on consumer spending patterns to help determine what products to sell and to better target their marketing efforts.
  • Weather models use vast amounts of data to predict catastrophic events and provide early warning to affected residents.
  • Investment firms rapidly collect and analyze market and financial data to make quick investment and hedging decisions.
  • Consulting firms assist in determining if data breaches have compromised personal data in companies.
  • Credit agencies analyze purchasing patterns to assess the risk of identity theft and help protect consumers.

Predictive analytics is also used in the analysis of defensive weapon systems, discovery of new energy sources, improvement of inventory tracking systems, and enhancement of air traffic control systems.  This is only a sample of the increasing usage of predictive analytics in growing areas.

The RMU Advantage

  • The RMU statistics and predictive analytics provides students with the ability to analyze large sets of data in a useful way to make predictions and assist in the decision making process.
  • RMU's predictive analytics curriculum is specifically designed to prepare students with hands on experience in working with large data sets.  Courses include extensive topics in both database management and statistical analysis.
  • The degree is closely related to RMUa's widely acclaimed actuarial science program with a variety of common courses.  Further, many insurance companies with experience in hiring RMU actuarial science students are taking advantage of information derived from large data sets and will be looking for students in the area of analytics.
  • Classes are small and informal, taught by experienced professors dedicated to undergraduate education.
  • Training to use technology begins in the freshman year and is integrated throughout the curriculum. Students gain the skills needed to apply technology in the classroom and the workplace. 

Curriculum

The 120-credit hour curriculum has three components:

1. Robert Morris University Core:  40 credits

These are the traditional liberal arts requirements of the University. Studies in humanities, communications skills, and social, behavioral, natural and quantitative sciences are included.

2. Major Courses:  65 credits

This component includes courses in accounting, finance, mathematics, statistics, microeconomics, and information systems.

3. Open Electives:  15 credits

Students may select courses within University offerings to broaden their skills in some area of interest.


Statistics and Predictive Analytics as a Career

In the four previous editions of the CareerCast.com, dating back to 2014, statistician and/or data scientist has never been rated lower than fourth. In both 2016 and 2017, statistician was ranked in the top two professions and in 2016, data scientist and statistician were ranked #1 and #2 respectively.  The editors compile statistics on 200 occupations and rank them based on four key criteria: environment, income, employment outlook, and, stress. The data comes from government sources, such as the U.S. Bureau of Labor Statistics as well as studies from trade associations and industry groups.

Preparing for RMU's Statistics and Predictive Analytics Degree

Students seeking to major in statistics and predictive analytics should take as many high school mathematics and computer science courses as possible. A strong background in all areas of pre-calculus mathematics and any programming/database courses provides an excellent basis for university work. Students also should have an interest in developing management and communications skills. Students planning to transfer college credits to RMU should complete courses in calculus, introductory economics, accounting and other business-related areas.

Concentrations