Data Analytics Major (BS)

Data analytics is the process of reviewing (possibly extremely large) sets of raw data, preparing it for analysis, using mathematical and statistical techniques combined with programming and software applications to spot trends and other behavior, and presenting the analysis in a way that allows for actionable forecasting and assessment. This is an interdisciplinary field
that combines statistics, mathematics, computer programming, information technology, and business administration.

Data Analytics Major
Major Requirements: Forty-seven (47) semester hours
Required courses:

  • BS201 Principles of Management (3)
  • BS202 Principles of Marketing (3)
  • BS484 Business Research and Methodology (3)
  • CS154 Database (1)
  • CS170 Principles of Operating Systems (3)
  • CS180 Structure and Logic (4)
  • CS182 Data Structures with C# (4)
  • CS242 Database Theory (3)
  • MS121 Calculus I (4)
  • MS122 Calculus II (4)
  • MS232 Linear Algebra (3)
  • MS252 Statistics (3)
  • MS282 Applied Statistics with R (3)
  • MS340 Linear Regression (3)
  • MS440 Data Analytics Project (3)

Students are strongly encouraged to complete an internship as part of their program of study. Students will also be encouraged to consider a minor in Business Administration, with BS305 being one of the chosen electives. Any student considering a career as an actuary or a graduate program in statistics will be encouraged to also take MS231, MS493, and MS494.

Courses

  • BS201 Principles of Management (3) SS1

    The focus is on the study of the origin and development of management theory, processes of management, decision-making, leadership, communication, social responsibility, and international management. Emphasis on application of management principles to managing organizations.

  • BS202 Principles of Marketing (3) SS1

    An introduction to basic marketing concepts, including marketing strategy, pricing, promotional activities, product development, and physical distribution. Sophomore status required for traditional age students. Recommended: ES 211.

  • BS484 Business Research and Methodology (3)

    A market-oriented introduction to business research. Subjects covered include the translation of a management problem to a research problem, implementation issues in business research, including basic statistical procedures, and the communication of research results to management.Prerequisites: BS201, BS202, MS151.

  • CS154 Database (1)

    This hands-on lab course covers basic database and file management functions using Microsoft Access. It is a software application class, not a programming course, and introduces skills such as creating reports, setting up input forms, and looking up database information. Database software packages are used to create and manage data files such as employee records, inventory files, names and addresses, and business contact lists. This course would be beneficial to students of all backgrounds.

  • CS170 Principles of Operating Systems (3)

    Fundamental concepts in operating systems and how they are used in computing will be explored. Hands-on exposure to Windows and a UNIX-type operating system are included. A study of disk layouts and management as well as memory management will be presented. Windows and UNIX command prompt manipulation will complete the requirements. Co-requisite of CS180 recommended.

  • CS180 Structure and Logic (4)

    Fundamental concepts in structured object-oriented programming. Structures include sequence, selection, repetition, writing, and the use of methods and objects. Programs will be designed using the Warnier-Orr diagramming tool. Designs will be coded, debugged, and tested using a programming language. Co-requisite of CS170 recommended.

  • CS182 Data Structures with C# (4)

    Programs using classes, objects, error handling, arrays, and array-based lists will be designed coded, debugged, and tested using the Windows GUI interface and the C# programming language. Prerequisites: MS151, CS180.

  • CS242 Database Theory (3)

    Introduction to concepts and technology of database management systems; physical data organization; hierarchical, network, and relational models; reading and writing basic structured query language (SQL) statements using a commercial relational database management system. Prerequisites: CS154, CS170, CS180.

  • MS121 Calculus I (4) MS

    Functions, limits, continuity, derivatives, antiderivatives, Fundamental Theorem of Calculus, solids of revolution. This course has five contact hours per week. Prerequisites: Three and one-half years of college-preparatory math, including trigonometry or MS114.

  • MS122 Calculus II (4) MS

    Inverse functions, integration techniques, integrals with applications, conic sections, polar coordinates, parametric equations, sequences and series. This course has five contact hours per week. Prerequisites: MS121

  • MS232 Linear Algebra (3) MS

    Systems of equations, matrices, determinants, vector spaces, linear transformation, eigenvalues, eigenvectors, and canonical forms. Prerequisite: MS122.

  • MS252 Statistics (3)

    Designed for students who have had at least three (3) years of high-school mathematics or its equivalent. Topics to be covered include frequency distributions, variability, probability, sampling, estimation, testing, hypotheses, analysis of variance, regression and correlation analysis, and nonparametric tests. (Course counts as three (3) semester hours toward a minor, but only one (1) semester hour toward a major.) Prerequisite: MS114.This course is not accepted for the General Education Mathematics requirement.

  • MS282 Applied Statistics with R (3) MS

    The course is designed to provide participants with a basic understanding of common statistical computing approaches and how to apply those approaches to common industry and research scenarios. Following completion of the course, students will possess the requisite programming skills to function as a programmer analyst in an analytical work environment. Topics include: importing/exporting data in various formats; character and numeric manipulation; merging; subsetting, and combining data sets; effective programing with common data structures; and producing high quality graphics and reports for end users. The free and open source R programming language will be used extensively throughout the course to teach fundamental programming concepts and applied statistical approaches. Introductory Statistics with R {Daalgard 2008} will serve as a supplemental text to aid in retention and understanding of the topics covered.

  • MS340 Linear Regression (3)

    The study of regression techniques and applications in statistics. Topics include linear regression, analysis of variance (ANOVA), multiple regression, analysis of covariance (ANCOVA), and linear hypotheses. Prerequisites: MS232 and at least one of MS252 and MS494. MS282 is recommended.

  • MS440 Data Analytics Project (3) MS

    An application of foundational data analytics skills to a real-life project. The course will include explorations of specific examples of data analysis problems that will serve to exercise and integrate students’ backgrounds in linear algebra, applied statistics, probability, and programming. Additionally, students will become familiar with good data visualization practices using appropriate software as well as other software tools for managing data. The course will culminate with an analytics project and presentation using real-world data. Prerequisites: CS180, MS232, MS252, and junior or senior standing.