Bachelor of Science Applied Statistics With Computing
PREAMBLE
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 affects 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. Statistical methods are exclusively used 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. Investigator’s efforts to learn about a specific phenomenon, be response of a patient to a certain medical treatment or the effectiveness of a particular instructional program on student’s learning, are impacted by the presence of natural variation. The field of statistics is concerned with valid and efficient way to learn more about these phenomena in the presence of such variation.
The statistician’s task is to determine what data to collect, how to collect and how to analyze. These problems are discussed under design of Experiments and Sample Surveys. Statistical inference is concerned with inferring what the population is like on basis of the sample. The link between population and sample is provided by Probability Theory, which forms an important part of the curriculum. Developing and assessing statistical models to describe the variation in some response in terms of other explanatory variables and applications of these models is discussed.
Other areas in Pure and Applied Mathematics that find applications in Statistics include Calculus, Linear and Abstract algebra, Combinatory, Difference and Differential equations. Since a statistician requires a background courses in computer programming and applications are incorporated.
PROGRAMME OBJECTIVES
PROGRAMME OBJECTIVES
The objectives of the B.Sc. in Applied Statistics with Computing program are to produce graduates that are able to:

Design methods for collecting and interpreting data.

Apply statistical techniques to model relationships between variables and make predictions.

Design research system and effectively analyze the resulting data.
To be admitted into the B.Sc. (Applied Statistics with Computing) program, a candidate must satisfy the minimum University entry requirements. In addition, candidates must satisfy the following subject cluster:

Mathematics OR Mathematics

Any group II Physical Science

Any group III Biological Science

Any from Group II/III /IV/V Geography/Accounts/Commerce
Course duration
The duration of the program shall normally take four academic years.
A candidate should take a minimum of at least 21 units or at most 24 units per semester.
In addition to the normal semesters, there are field visits and industrial attachments at selected industrial, educational or research establishments. The attachment course shall normally be taken at the end of third year of study.
Examinations
The University Common Rules and Regulations for Under Graduates Examinations shall apply.
Course Structure
First Semester
Code

Description

Units

COM

INTRODUCTION TO COMPUTERS AND COMPUTING

3

PHY 110

BASIC PHYSICS 1

4

COM 111

COMPUTER APPLICATIONS

3

MAT 110

BASIC CALCULUS

3

IRD 100

COMMUNICATION SKILLS I

3

IRD 101

QUANTITATIVE SKILLS I

3

COM 113

MATHEMATICS FOR COMPUTER SCIENCE I

3

TOTAL


22

Second Semester
Code

Description

Units

PHY 111

BASIC PHYSICS II

4

MAT 111

GEOMETRY AND ELEMENTARY APPLIED MATHEMATICS

3

COM 120

SYSTEM HARDWARE

3

COM 121

PROCEDURAL PROGRAMMING I

3

IRD 102

COMMUNICATION SKILLS I

3

IRD 103

DEVELOPMENT CONCEPTS AND APPLICATIONS

3

COM 123

MATHEMATICS FOR COMPUTER SCIENCE II

3

TOTAL


22

First Semester
Code

Description

Units

COM 210

PROCEDURAL PROGRAMMING II

3

COM 211

SYSTEM SOFTWARE

3

COM 212

DIGITAL ELECTRONICS I

3

COM 215

ELECTRICAL CIRCUITS

3

COM 217

ELECTRONICS 1

3

IRD 104

QUANTITATIVE SKILLS II

3

COM 216

INTERNET FUNDAMENTALS

3

TOTAL


21

Second Semester
Code

Description

Units

STA 216

Mathematical Statistics II

3

STA 217

Principle of Statistical Inference

3

STA 218

Introduction to Time Series Analysis

3

STA 219

Categorical Data Analysis

3

MAT 213*

Linear Algebra II

3

MAT 216

Real Analysis

3

COM121*

Procedural Programming I

3

TOTAL


21

First Semester
Code

Description

Units

STA 315

Mathematical Statistics III

3

STA 316

Applied Regression Analysis I

3

STA 317

Theory of Estimation

3

STA 318

Computing Methods and Data Analysis

3

MAT310*

Advanced Real Analysis

3

MAT 314*

Ordinary Differential Equations

3

IRD 305*

Entrepreneurship for Small Business

3

TOTAL


21

Second Semester
Code

Description

Units

STA 319

Sampling Theory and Methods I

3

STA 320

Design and Analysis of Experiments I

3

STA 321

Testing of Hypotheses

3

STA 350

Industrial Attachment

6

COM 318*

Database Systems

3

MAT 317*

Numerical Analysis I

3

TOTAL


34

ANY ELECTIVE 3

ELECTIVES

STA 322

Applied Statistical Inference

3

STA 323

Survey Research Methods

3

STA 324

Introduction to Mathematical modeling

3

STA 325

Econometric Models

3

STA 326

Statistical Quality control Methods

3

STA 327

Operations Research II

3

STA 328

Applied Regression Analysis II

3




First Semester
Code

Description

Units

STA 418

Applied Time Series Analysis

3

STA 419

Introductions to Measure and Probability

3

STA 420

Statistical Demography

3

STA 421

Statistical Computing

3

STA 422

Design and Analysis of Experiments II

3

STA 450

Statistical Consulting Project

3

IRD400*

Development project Appraisal

3

TOTAL


21

Second Semester
Code

Description

Units

STA 423

Biometry Methods

3

STA424

Stochastic Processes

3

STA 425

Sampling Theory and Methods II

3

COM400*

Computer Programming II

3

ANY THREE ELECTIVES 9

TOTAL


21

ELECTIVES

STA 426

Bayesian Inference and Decision Analysis

3

STA 427

Survival Models and Analysis

3

STA 428

Mathematical Application in Finance

3

STA 429

Applied Multivariate Analysis

3

STA 430

NonParametric and Robust Methods

3

STA 431

Principles of Actuarial Science

3

STA 432

Statistics for National Planning

3

STA 433

Operation Research III

3






