Analytics Major

Bachelor of Science in Analytics

Ethical principles

1. PHIL 241

   Ethics In a Digital World
   4

Conceptual data understanding

1. ECON 222

   Microeconomic Principles: Public Policy. 4. The study of economics; supply and demand; consumer behavior; firms, production and cost; perfect competition, monopoly and other market types; income distribution; all explained with the goal of understanding economic problems and evaluating public policy to solve these problems. Applications to agriculture, energy, environment, poverty, economic development, discrimination, natural resources, taxes, regulation, sports and other special topics, depending on the semester. May be taken independently of ECON 221. Fulfills social science and social justice/ environmental responsibility requirements (1998). Social/behavioral science, evaluating systems and environments, and numerical/symbolic engagement requirements

   As published: “Microeconomic Principles: Public Policy”
   2019
2. ECON 311

   Data Collection & Analysis. 4. Students will use a variety of key economic sources and learn various techniques of univariate analysis. They will gain experience in developing testable hypotheses, creating well-designed survey instruments to test these hypothesis, and gaining experience in different methods of data presentation. Fulfills social/behavioral science requirement

   As published: “Data Collection & Analysis”
   2019

Data organization

1. CTIS 210

   Introduction to Computer Programming. 4. Exploration of computer programming with emphasis on scientific, educational and entertainment applications. Topics include programming fundamentals, user interaction, graphics display, data processing, problem solving and artificial intelligence. Prior programming experience not required.Prerequisite: Background in using computers at the level of an introduction to computers course or equivalent experience, and mathematics background at the level of college algebra. Fullfills numeric/symbolic engagement

   As published: “Introduction to Computer Programming”
   2019
2. CTIS 342

   Database Systems. 4. Introduction to theory and practice of enterprise-level relational database systems. Using a database engine, students will learn the principles of entity relationship modeling and normalization. By modifying a database in a project, students will learn how to create queries using SQL, triggers, stored procedures, cursors, forms and reports.Prerequisite: CTIS 210 and BUS 243 or CTIS 243

   As published: “Database Systems”

   or: CTIS 331 Information Design
3. CTIS 243

   Management Information Systems (BUS 243). 4. Introduction to the management of computing and information resources in organizations. Course topics include computer hardware and software, telecommunications, database management, electronic commerce and business intelligence. Students explore information technology and business problems and use spreadsheet and database applications to create effective solutions.Prerequisite: Background in using computers at the level of an introduction to computers course or equivalent experience. Fulfills business and policy studies requirement (1998). Social/ behavioral science requirement

   As published: “Management Information Systems (BUS 243)”

   or: GEOL 215 Data Wrangling
   2019

Data modeling

1. MATH 112

   Elementary Statistics. 4. Descriptive statistics; probability and probability distributions; sampling and sampling distributions; confidence intervals and hypothesis testing; correlation and regression analysis. Emphasis on application and interpretation. Recommended for social science and pre-professional majors; does not count toward the major. Fulfills numeric/symbolic engagement requirement. Offered in 14-week semesters

   As published: “Elementary Statistics”
2. ECON 312

   Econometrics. 4. Students will learn and apply multivariate analysis as they test specific economic models or theories of their choice. They will gain confidence as they interpret the results and problem solve any challenges that emerge from their analysis. Fulfills the Senior Seminar requirement for the Integrative Experience.Prerequisite: Econ 311

   As published: “Econometrics”

Analysis/applications

1. MATH 241

   Scientific Computing. 4. Scientific Computing is a course designed jointly by Math & Physics faculty to serve students of the sciences. We will use the programming language Python and a variety of the standard libraries (especially numpy, matplotlib, vpython) to do analyses and simulations. Emphasizes the documentation and presentation of results to peers. Satisfies elective credit for Analytics major. Taught in the 3-week semester

   As published: “Scientific Computing”
2. ECON 328

   Analytics for Business and Government (ACCT 328 or MATH 328). 4. This course is a hands-on introduction to business analytics. In this course, students will learn to convert quantitative data into information that can be used to help guide business/government decision making. This course provides students with the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations. Students will apply modern data mining tools to various data sets in an analytical software environment. Emphasis is placed on concepts, applications, and interpretation of results as wellas professional skills like communication, teamwork, and presentation.Prerequisite: ECON 222 or permission of instructor

   As published: “Analytics for Business and Government (ACCT 328 or MATH 328)”

Elective (select 1 course)

1. MATH 220

   Calculus I. 4. Limits, derivatives, and integrals of functions of a single variable with applications to optimization. Fulfills numeric/ symbolic engagement requirement.Prerequisite: MATH 114 College Algebra MATH 116 Trigonometry or MATH 115 Elementary Functions or equivalent high school credit

   As published: “Calculus I”
2. MATH 222

   Calculus II. 4. Techniques of integration, indeterminate forms, infinite series - including Taylor series. Applications to differential equations, physical systems, and probability.Prerequisite: MATH 220 Calculus I or AP Calculus AB Fulfills numeric/symbolic engagement requirement

   As published: “Calculus II”
3. MATH 310

   Probability and Statistics. 4. Fundamentals of the analysis and interpretation of statistical data, theory and application. Includes descriptive statistics; probability; discrete and continuous random variables, their probability, density and moment-generating function; joint, marginal and conditional probability and density functions of several random variables; sampling distributions; estimation; hypothesis testing. Fulfills quantitative literacy requirement (1998).Prerequisite: MATH 222 Calculus II, AP Calculus BC, or permission of the instructor

   As published: “Probability and Statistics”
4. CTIS 310

   Advanced Computer Programming. 4. A continuation of the study of program development begun in CTIS 210. The main areas of study are advanced programming features such as recursion and dynamic memory; a further investigation into object-oriented principles such as object-oriented design, inheritance and polymorphism; an introduction to simple data structures ? lists, queues, stacks and binary trees; and an introduction to algorithm analysis using searching and sorting algorithms.Prerequisite: CTIS 210

   As published: “Advanced Computer Programming”

another course from listed above not used to satisfy the major requirements

Capstone project

The project can be carried out independent of or within a 400-level course:

MYCQ contribute course

Independent study