Minor in Business Analytics
Data science is changing the world. Businesses rely on data to spark new ideas, to provide innovative solutions and to make strategic industry decisions. Learning why data matters and how to use it effectively can make you an influential leader in the marketplace. Biola’s business analytics minor shows students the real-world applications of data and how data drives both business and innovation. Students will be equipped to collect, evaluate and use data to help businesses become smarter, more strategic and better stewards of their resources. In Fall 2019, Biola will open a brand new, state-of-the-art analytics lab which will be a place of collaboration and networking for students. Learn from professors across disciplines that will challenge you to think critically and demonstrate how biblical principles apply to business practices. You’ll be ready to enter into a fast-growing career field and pursue careers such as a business systems analyst, data analyst and business intelligence manager.
Note: This list is intended to give you a quick glimpse into the program’s academic offerings, and should not be used as a guide for course selection or academic advising. For official program requirements, see the course catalog.
You must choose one of the mathematics courses listed below as a part of your minor: MATH 190, MATH 210 or MATH 318
|BUSN 211||Principles of Accounting I|
|Financial accounting concepts and techniques essential for all business majors and those seeking to learn the language of business; analyzing and recording transactions; preparation of financial statements; valuation and allocation procedures. Grade Mode: A.|
|BUSN 220||Management Information Systems|
Students will study Information systems, their design, implementation and contribution to management planning, decision-making and control. The impact of information systems on the personal and spiritual lives of students as well as their impact on broader society will also be covered. Students will learn relevant business software applications through hands-on lab assignments. Grade Mode: A.
|BUSN 323||Business Analytics|
|Students will be introduced to the concepts of business analytics. Topics will include business modeling, optimization techniques, advanced spreadsheet techniques, and data visualization. Grade Mode: A.|
|BUSN 370||Business Finance|
An examination and evaluation of financial decision making in the Corporate environment valuing future cash flows, characterizing risk and return and evaluating options available to firms to finance their operations or fund growth opportunities. Students will learn how to analyze financial data to provide information to management on how to improve the financial performance of their firm. Grade Mode: A.
|BUSN 423||Advanced Business Analytics|
|This course will continue to prepare students for a career in business analytics. Using case studies, students will synthesize and apply a variety of business analysis methodologies. Students will learn needed database concepts, data mining methods, and other digital technologies needed to work with large, unstructured data sets. Grade Mode: A.|
|CSCI 105||Introduction to Computer Science|
|Introduction to computer hardware and software. Problem solving methods. Elementary concepts of algorithm development. C++ programming. Lecture/Lab Hours: Three hours lecture, one hour lab. Grade Mode: A.|
|MATH 190||Business Statistics|
|Collection and presentation of business data, central tendency and dispersion measures for business analysis, sampling and inference for confidence intervals and hypothesis testing, business forecasting with simple and multiple regression, index numbers. Notes: Approved for Core Curriculum Math credit. Grade Mode: A.|
|MATH 210||Introduction to Probability and Statistics|
|Nature of statistical methods, description of sample data, fundamental concepts of probability, probability distributions, sampling, estimation, correlation and regression, application of same. Notes: Approved for Core Curriculum Math credit. Grade Mode: A.|
|Prepares the student for biostatistical application essential to practice in evidence-based professions. Content includes: descriptive statistics; probability theory and rules; discrete and continuous probability distributions; sampling distributions; confidence intervals; hypothesis testing; experimental design; ANOVA; linear and multiple regression; contingency table analysis; non-parametrics; survival analysis; discussion of the use of statistics in journal articles. Notes: Approved for Core Curriculum Math credit. Credit given for only one of 210 and 318. Grade Mode: A.|