Each student who has completed an application for admission and provided his/her high school transcript(s) and test score(s) is reviewed for eligibility to participate in the four-year BBA/MBA track. Admission to the BBA/MBA track from high school requires one of the following conditions:
3.25 Cumulative GPA (CGPA) with 25 ACT/1210 SAT, or
3.50 Cumulative GPA (CGPA) with no test score
A transfer student may also be eligible to participate in the four-year BBA/MBA track if, upon attending college-level institutions, he/she maintained an overall 3.25 GPA, earned a total of 23 credits or less (excluding Advanced Placement and dual enrollment credits) and, upon graduating from high school, met one of the criteria indicated above.
Each eligible student is mailed additional BBA/MBA and Honors Program materials with details on accessing the four-year BBA/MBA track Conditions of Acceptance and Enrollment Form. A completed BBA/MBA Enrollment Form must be received in order for a student to be officially enrolled in the four-year BBA/MBA track and register for the respective courses. The student is accepted into the four-year BBA/MBA track as a freshman and receives a provisional acceptance to the DeVos MBA program.
|
Exam |
Minimum Score |
|
|---|---|---|
|
Undergraduate Programs |
Graduate Programs |
|
|
TOEFL |
61 (iBT) |
80 (iBT) |
|
IELTS |
6.0 overall band score |
6.5 overall band score |
|
EIKEN |
Grade 2A |
Grade Pre-1 |
|
IB |
5 on English A1 or A2 exam |
N/A (not accepted for Graduate admission) |
|
Cambridge English Tests |
FCE or CAE (minimum score of B2) |
CAE or CPE (minumum score of C1) |
|
ELS |
Level 112 |
Level 112 |
|
ACT/SAT |
ACT - 18 for both composite and English sub-score |
N/A (not accepted for Graduate admission) |
|
PTE Academic |
50 |
58 |
|
GTEC |
1126 |
1201 |
The Business Analytics minor will meet the growing need for managers who need to make decisions based upon the methods of data analytics. This includes Data Mining and the ability to collect, analyze, and interpret what is commonly referred to as Big Data. The resulting skill set will include the ability to predict consumer behavior using predictive analytics. Emphasis will be on application and interpretation of statistical techniques and business analytics approaches. Students in any of our disciplines would benefit from this curriculum at Northwood University.
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MTH 3340 Statistics II (3 credits)
A continuation and expansion of concepts covered in MTH 2310. It includes hypothesis testing of proportions, means and variances of one and two populations, including matched pairs, correlation, simple linear regression, chi-square tests, multiple regression, forecasting, statistical process control, and analysis of variance. Appropriate technology and/or software will be required.
Prerequisite: MTH 2310
MTH 3400 Introduction to Data Science (3 credits)
This survey course will introduce students to the concepts and principles of Data Mining industry standards like CRISP-DM and SEMMA. This includes the conceptualization of data, information and knowledge, introduction of data collection, storage and preparation, database management, data visualization, and statistical data-driven decisions for solving business problems.
Prerequisites: MIS 1500 and MTH 2310
MIS 3200 Database Design and Implementation (3 credits)
The design, implementation, and maintenance of databases play a key role in the success of modern information systems. Students examine the logical design and physical organization of data in an enterprise database. Various approaches to data management are covered including relational database management systems. Topics include the advantages of using database management systems, the proper design and implementation of a database, accessing and manipulating data using Structured Query Language (SQL), and the role of a database administrator.
Prerequisite: MIS 2140
MTH 4100 Data Mining and Modeling for Business Decisions (3 credits)
In this course students will apply quantitative methods such as linear, logistic, and multiple regression; time series forecasting, find optimal solution for goals, use decision trees, and apply simulation to business problems.
Prerequisites: MIS 1500 and MTH 2310
MTH 4200 Predictive Analytics (3 credits)
Students will apply the concepts, principles and analysis skills of Data Mining to build predictive models. This course will require the planning, implementation, and evaluation of a solution to a business case problem.
Prerequisites: MIS 1500 and MTH 2310
AMM 3050 Category Management (3 credits)
Project-based, cross-disciplinary course focusing on the application of general business concepts taught using an experiential model. Problem-solving and situation/scenario analysis will be explored utilizing industry case studies and real-world situations. Students will learn and experience making fact-based decisions using industry data and tools.
Prerequisites: MIS 1050 or 1500, MTH 2310 and MKT 2080
MIS 3300 Project Management (3 credits)
Students will examine the significant role that project management plays in the successful completion of an information technology project. The skills, tools, and best practices used to effectively manage a project from its inception to successful closure will be discussed. Students will learn how to control the scope, time, cost, and quality of projects, and gain hands-on experience using project management software.
Prerequisite: MIS 1500
OPS 2350 Statistics for Quality Engineering (3 credits)
This course applies the concepts of Statistics to the quality management functions within an organization. When students have completed this course, they will be prepared to succeed on the American Society for Quality Certified Quality Engineer exam. Topics covered will include: Introduction to Quality Management, Quality Systems Requirements, Measurement Systems Analysis; Process Capability Analysis; Process Control; and Reliability and Risk Management.
Prerequisite: MTH 2310 and MTH 3340
OPS 4100 Statistics for Continuous Improvement (3 credits)
This course will provide hands-on experience in the arena of Designed Experiments for process improvement and optimization. The DMAIC (Design, Measure, Analyze, Improve, Control) process will be covered in detail. Students will learn to identify sources of variation, analyze variation, reduce variation, and tie these concepts to Six Sigma methodology which can be applied in any business setting and to any business process. When the course is successfully completed, students will be prepared to be examined for Six Sigma Green Belt certification.
Prerequisite: OPS 2350
OPS 4200 Lean Six Sigma (3 credits)
This course will provide an overview of the principles of Lean manufacturing, both internal at a company and throughout its supply chain. Topics covered will include value stream mapping and identifying waste. Students will gain experience with pull production/ just-in-time continuous flow systems. They will develop an understanding of the relationship between reducing work in process inventory and managing quality. The relationship between lean manufacturing and six sigma implementation will also be explored.
Prerequisite: OPS 2350
Other departments may develop courses in the future that could be applied to this minor.
MIS 1500 Business Productivity Software
MTH 2310 Statistics I Descriptive Statistics and Probability
In order to earn a Minor in Business Analytics, you will be required to complete a core of 5 courses and 1 or more electives.
Complete all 5 courses.
MTH 3340 Statistics II Inference
MTH 3400 Introduction to Data Science
MIS 3200 Database Design and Implementation
MTH 4100 Data Mining and Modeling for Business Decisions
MTH 4200 Predictive Analytics
Select at least 1.
AMM 3050 Category Management
MIS 3300 Project Management
OPS 2350 Statistics for Quality Engineering and Improvement
OPS 4100 Statistics for Continuous Improvement (Measurements and metrics)
OPS 4200 Lean Six Sigma (Process Improvement Approaches)
