Bachelor of Science in Applied Statistics

Statistics is an inductive science in which information is extracted from sample data in order to draw inferences. This most often involves planning experiments to ensure that valid answers to questions are obtained from the sample. Statistics is a subject that deals with the collection and analysis of data and affect most aspects of modern life. It is a subject that derives vitality in coping with practical problems, which arises in all fields of scientific activities.

Applied statistics is the root of data analysis, and the practice of applied statistics involves analyzing data to help define and determine business needs. With today?s increased access to big data, companies are looking for statisticians, data analysts, data scientists, and other professionals with applied statistics knowledge who can visualize and analyze data, make sense of it all, and use it to solve real-world problems.

Statistical methods are exclusively used in Biological and Physical Sciences, Agriculture, Business, Finance, Economics, Engineering, and many other fields. It deals rationally and objectively with the uncertainty that accompanies variation phenomena as highly complex as the interplay of many factors that affects our environment.

Applied statisticians apply their knowledge of statistical methods to a variety of subject areas, such as biology, economics, engineering, medicine, public health, psychology, marketing, and education.

This BSc degree in Applied Statistics is structured to provide fundamental knowledge of the application of statistics in these fields. The program covers five major areas of Applied Statistics, namely:

• Mathematical Statistics
• Economic Statistics
• Demography and Social Statistics
• Actuarial Science
• General Applied Statistics.

Objectives of Bachelor of Science in Applied Statistics

The BSC in Applied Statistics prepares students to meet today?s surging demand for data experts. The program combines statistics theory and methodologies with emerging technologies and teaches students how to take real data and interpret it in an efficient manner.

The main objectives of this BSC in Applied Statistics programme are to:

• equip the student with a broad-based statistical knowledge and skills;
• train statisticians for employment in public and private sectors.
• prepare candidates for postgraduate studies in statistics

BSC in Applied Statistics graduates will be able to apply statistics to solve practical problems in today?s data-centric world. They decide what data they need to collect and how to collect that data; and then they analyze and interpret it using statistical tools, algorithms, and software. 

What you will study

This Bachelor of Science in Applied Statistics course covers statistical theory, statistical inference, probability theory, data mining and visualization, programming languages, and more.

The units covered include:

First Year, First Semester

• Introduction to Computer and Computing
• Basic Physics 1
• Computer Applications
• Basic Calculus
• Communication Skills 1
• Quantitative Skills 1

First Year, Second Semester

• Basic Physics II
• Geometry and Elementary Applied Mathematics
• System Hardware
• Procedural Programming
• Communication Skills 1
• Development Concepts and Applications
• Mathematics for Computer Science

Second Year, First Semester

• Procedural Programming
• System Software
• Digital Electronics
• Electrical Circuits
• Electronics 1
• Quantitative skills II
• Internet Fundamentals

Second Year, Second Semester

• Mathematical Statistics II
• Principle of Statistical Inference
• Introduction to Time Series Analysis
• Categorical Data Analysis
• Linear Algebra II
• Real Analysis
• Procedural Programming I

Third Year, First Semester

• Mathematical Statistics III
• Applied Regression Analysis I
• Theory of Estimation
• Computing Methods and Data Analysis
• Advanced Real Analysis
• Ordinary Differential Equations
• Entrepreneurship for Small Business

Third Year Second Semester

• Sampling Theory and Methods I
• Design and Analysis of Experiments I
• Testing of Hypotheses
• Industrial Attachment
• Database Systems
• Numerical Analysis I

Electives

• Applied Statistical Inference
• Survey Research Methods
• Introduction to Mathematical modeling
• Econometric Models
• Statistical Quality control Methods
• Operations Research II
• Applied Regression Analysis II

Fourth Year, First Semester

• Applied Time Series Analysis
• Introductions to Measure and Probability
• Statistical Demography
• Statistical Computing
• Design and Analysis of Experiments II
• Statistical Consulting Project
• Development project Appraisal

Fourth Year, Second Semester

• Biometry Methods
• Stochastic Processes
• Sampling Theory and Methods II
• Computer Programming II

Electives

• Bayesian Inference and Decision Analysis
• Survival Models and Analysis
• Mathematical Application in Finance
• Applied Multivariate Analysis
• Non-Parametric and Robust Methods
• Principles of Actuarial Science
• Statistics for National Planning
• Operation Research III