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Bachelor of Science in Statistics and Data Analytics
The undergraduate B.Sc. program in Statistics and Data Analytics at UAEU introduces the concepts, methods, and tools of collecting, processing, and analyzing data. The objective is to discover hidden patterns in data and generate actionable insights. Building on the fundamental concepts of probability and statistical inference (i.e., estimation & hypothesis testing), the program provides the fundamental background, as well as the modern techniques for statistics and data analytics. Two distinctive features of the program are: the emphasis on real-world applications; and the enrichment of lecture materials through practical experience with state-of-the-art computer software and modeling languages.
Program Objectives
- Knowledge and skills in statistical, analytical and mathematical modeling, computing, and problem solving.
- Critical thinking, research, and analytics skills to gather data and information and solve problems involving big and/or complex data.
- Effective study & communication skills.
- Work productively in teams.
- Independence and ethical and social awareness at the local and global level.
Program Learning Outcomes
Upon successful completion of this program, students will be able to:
- Demonstrate a comprehensive knowledge of concepts of statistics and data analytics, and the application of the concepts for problem solving using real-world data.
- Integrate modeling and computational skills in statistical and data analytics, for developing comprehensive solutions to data-driven problems.
- Effectively communicate to specialized and non-specialized audiences, orally, visually, and in writing, the results and interpretation of statistical and computational analyses.
- Apply teamwork skills and creativity, and demonstrate autonomy and responsibility, in undertaken tasks and projects.
- Demonstrate independence and ethical awareness towards issues in statistics and data analytics, such as data ownership, security and sensitivity of data, privacy concerns in data analysis, and transparency and re-producibility.
Degree Requirements
Required Credit Hours : minimum 121 hours
General Education (req. CH:33) Cluster 1: Skills for the Future (Req. Ch:15)
| Area 1: Innovation and Entrepreneurship (3 hours ) | Credit Hours | |
|---|---|---|
| GEIE222 | Fundamentals of Innovation and Entrepreneurship | 3 |
| Area 2: English Communication (3 hours ) | Credit Hours | |
|---|---|---|
| ESPU104 | Introduction to Academic English For Business | 3 |
| Area 3: Fourth Industrial Revolution (3 hours ) | Credit Hours | |
|---|---|---|
| GEIT112 | Fourth Industrial Revolution | 3 |
| Area 4: Critical Thinking (3 hours ) | Credit Hours | |
|---|---|---|
| CSBP119 | Algorithms and Problem Solving | 3 |
| Area 5: Quantitative Reasoning (3 hours ) | Credit Hours | |
|---|---|---|
| MATH105 | Calculus I 1 | 3 |
1 : Also counts towards the Major | ||
Cluster 2: The Human Community (Req. Ch:12)
| Area 1: Humanities and Fine Arts (3 hours ) | Credit Hours | |
|---|---|---|
| ARCH366 | History and Theories of Contemporary Architecture | 3 |
| HSR120 | Introduction to Heritage & Culture | 3 |
| HSR130 | Introduction to Language & Communication | 3 |
| PHI101 | Introduction to Philosophy | 3 |
| Area 2: Social and Behavioral Sciences (3 hours ) | Credit Hours | |
|---|---|---|
| ECON105 | Principles of Microeconomics 2 | 3 |
2 : Also counts towards the Major | ||
| Area 3: Emirates Society (3 hours ) | Credit Hours | |
|---|---|---|
| HSS105 | Emirates Studies | 3 |
| Area 4: Islamic Culture (3 hours ) | Credit Hours | |
|---|---|---|
| ISLM101 | Biography of the Prophet "Sira" | 3 |
Cluster 3: The Natural World (Req. Ch:6)
| Area 1: Natural Sciences (3 hours ) | Credit Hours | |
|---|---|---|
| ARAG205 | Introduction to Fish & Animal Science | 3 |
| ARAG220 | Natural Resources | 3 |
| BION100 | Biology and its Modern Application | 3 |
| CHEM181 | Chemistry in the Modern World | 3 |
| FDSC250 | Contemporary Food Science & Nutrition | 3 |
| GEOL110 | Planet Earth | 3 |
| PHED201 | Physical Fitness and Wellness | 3 |
| PHYS100 | Astronomy | 3 |
| PHYS101 | Conceptual Physics | 3 |
| Area 2: Sustainability (3 hours ) | Credit Hours | |
|---|---|---|
| GESU121 | Sustainability | 3 |
Research Learning Line
| Required Courses (9 hours ) | Credit Hours | |
|---|---|---|
| STAT102 | Business Statistics I | 3 |
| STAT202 | Business Statistics II | 3 |
| GBUS300 | Research Methods in Business and Economics | 3 |
Learning in Action
| Required Courses (18 hours ) | Credit Hours | |
|---|---|---|
| GBUS201 | Personal Development: Leadership and Team Competencies | 3 |
| GBUS301 | Personal Development: Career Preparation and Orientation | 3 |
| ENTR415 | Developing an Entrepreneurial Venture 3 | 12 |
| GBUS460 | Internship 4 | 12 |
3 : Students should take either ENTR 415 or GBUS 460 4 : The internship is conducted over 12 Weeks in the last semester (after a four week preparation session). No courses are allowed to be registered during the internship | ||
Business Core Requirements
| Required Courses (6 hours ) | Credit Hours | |
|---|---|---|
| BANA200 | Managing with Analytics | 3 |
| GBUS250 | Digital Economy | 3 |
Business Analytics Core Requirements
| Required Courses (6 hours ) | Credit Hours | |
|---|---|---|
| BANA250 | Business Intelligence | 3 |
| BANA310 | Data Management and Organization | 3 |
Statistics Core Requirements
| Required Courses (34 hours ) | Credit Hours | |
|---|---|---|
| MATH110 | Calculus II | 3 |
| MATH140 | Linear Algebra I | 3 |
| STAT230 | Principles of Probability | 3 |
| STAT240 | Data Exploration and Analysis | 3 |
| STAT300 | Introduction to Statistical Inference | 3 |
| STAT330 | Survey Methods | 3 |
| STAT360 | Applied Regression | 3 |
| STAT380 | Statistical Machine Learning | 3 |
| STAT400 | Applied Multivariate Analysis | 3 |
| STAT470 | Introduction to Statistical Computing | 3 |
| CSBP123 | Introduction to Programming | 4 |
Concentrations
| Students should select one concentration for total of 15 credit hours (15 hours ) | Credit Hours | |
|---|---|---|
Statistics Concentration
| Required Courses (9 hours ) | Credit Hours | |
|---|---|---|
| STAT430 | Categorical Data Analysis | 3 |
| STAT460 | Bayesian Statistics | 3 |
| STAT480 | Capstone in Statistics and Data Analytics | 3 |
| Elective Courses (6 hours ) | Credit Hours | |
|---|---|---|
| STAT250 | Statistical Graphics | 3 |
| STAT370 | Mathematical Statistics | 3 |
| STAT420 | Applied Time Series | 3 |
| STAT475 | Selected Topics in Statistics and Data Analytics | 3 |
Analytics for Business Concentration
| Required Courses (9 hours ) | Credit Hours | |
|---|---|---|
| BANA380 | Business Analytics | 3 |
| BANA400 | Business Analytics Applications | 3 |
| STAT482 | Capstone in Analytics for Business | 3 |
| Elective Courses (6 hours ) | Credit Hours | |
|---|---|---|
| BANA410 | Text Analytics | 3 |
| BANA420 | Graph Analytics | 3 |
| BANA430 | Applied Optimization | 3 |
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