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Bachelor of Science in Statistics

A undergraduate programme preparing students with the knowledge, practical skills and professional discipline required in Science in Statistics.

Bachelors

Bachelor of Science in Statistics

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01

Programme Overview

The Department of Economics and Statistics of Kampala International University recognizes the fact that students, regardless of their background in education, are supposed to have analytic approach both to normal life and academic atmosphere in order to have strong decision making ability. It is therefore the duty of this School to provide the students with the basic as well as advanced theoretical and practical knowledge of statistical principles in various analytical methods, and expose them to better awareness of the various factors that influence (or have influenced) modern approaches to descriptive and inferential statistics.The Bachelors degree of Statistics has been conceived in the light of the above. It is designed in response to the current demands for strong first degrees in terms of academic and professional content so as to enable the graduates to compete competently in the ever-thinning world market. The programme aims at producing professional Statisticians who are specialized and competent decision makers rich in content and professional knowledge. It takes into account the fact that recent global developments put heavy demands on the qualifications and continue to form a growing need for highly qualified people (Statisticians) to serve in their subject areas of specialization.PROGRAMME JUSTIFICATIONThe Department of Economics and Statistics is consciously aware that to be able to serve and indeed survive effectively in the rapidly changing competitive environment, the academic programmes offered must be designed and developed with the clear aim of meeting high academic and professional standards of the qualifications and products of the University.Kampala International University, like  any other institution of higher learning, must live up to this challenge by offering well articulated courses that will provoke the graduates to explore the heights in search for solutions to the many problems currently embedded in our education sector and the society as a whole. 

Teaching practiceConnect subject knowledge with classroom planning, assessment and learner support.
Education leadershipDevelop professional habits for school, community and education-sector service.
Research awarenessUse evidence, inquiry and analytical thinking to understand problems and propose solutions.
Career readinessPrepare for employment, further study, entrepreneurship and service in relevant professional settings.
02

What You Will Learn

By the end of the programme, students are expected to demonstrate the knowledge, practical skills and professional conduct required for effective work in Science in Statistics.

Subject masteryBuild strong knowledge in the teaching subjects and education foundations.
Teaching methodsPlan lessons, manage learning and use appropriate assessment approaches.
Learner supportRespond to diverse learner needs with inclusive and ethical practice.
School practiceConnect theory with school-based observation, teaching practice and reflection.
Research literacyUse inquiry to understand education problems and improve practice.
Professional identityDevelop communication, leadership and lifelong learning habits.
03

Course Structure and Learning Experience

The learning experience is organised to move students from foundational knowledge into applied, supervised and professionally oriented practice.

01

Education foundations

Students study the foundations of education, learning theory and subject content.

02

Methods and assessment

Training develops lesson planning, pedagogy, assessment and classroom communication.

03

School-based practice

Students connect theory with observation, practicum and guided reflection.

04

Research and improvement

The programme introduces inquiry, education research and improvement-focused thinking.

05

Professional formation

Students build ethical, inclusive and responsible teaching identities.

04

Course Content

39 courses 119 credit units

Academic Year 1

14 courses | 44 units
Semester 1
22 units
ECO 1101 Introduction to Microeconomics
4 units | Core
MAT1101 Introduction to Algebra and Logic
3 units | Core
MAT1102 Differential Calculus
3 units | Core
STA1101 Descriptive Statistics
3 units | Core
STA1102 Time Series and Index Numbers
3 units | Core
UCC 1100 Introduction to Computer Fundamentals
3 units | Core
UCC 1101 Introduction to English Language
3 units | Core
Semester 2
22 units
ECO 1201 Introduction to Macroeconomics
4 units | Core
ECO 1203 Principles of Development Economics
3 units | Core
ECO1202 Mathematical Economics
3 units | Core
MAT1202 Integral Calculus
3 units | Core
STA 1202 Statistical Inference I
3 units | Core
STA 1203 Introduction to Probability Theory
3 units | Core
UCC1202 Communication Skills
3 units | Core

Academic Year 2

14 courses | 42 units
Semester 1
21 units
COS 2101 Object Oriented Programming
3 units | Core
ECO 2101 Intermediate Microeconomics
3 units | Core
ECO 2102 Econometrics
3 units | Core
MAT 2101 Linear Algebra
3 units | Core
STA 2103 Statistical Inference II
3 units | Core
STA 2104 Probability Theory
3 units | Core
UCC2102 Research Methods
3 units | Core
Semester 2
21 units
ECO 2201 Intermediate Macroeconomics
3 units | Core
MAT 2102 Introduction to Numerical Analysis
3 units | Core
STA 2201 Non Parametric Statistics
3 units | Core
STA 2202 Analysis of Variance I
3 units | Core
STA 2203 Sampling Methods
3 units | Core
STA 2204 Time Series and Index Numbers II
3 units | Core
STA 2205 Data Analysis I
3 units | Core

Academic Year 3

11 courses | 33 units
Semester 1
15 units
ECO 3101 Advanced Microeconomics
3 units | Core
ECO 3104 Intermediate Econometrics
3 units | Core
STA 3101 Regression Analysis
3 units | Core
STA 3103 Data Analysis II
3 units | Core
STA 3105 Advanced Statistical Methods
3 units | Core
Semester 2
18 units
ECO3201 Advanced Macroeconomics
3 units | Core
STA 3204 Industrial Statistical Modeling
3 units | Core
STA3201 Analysis of Variance II
3 units | Core
STA3202 Advanced Econometrics
3 units | Core
STA3203 Multiple Regression and Correlation Analysis
3 units | Core
UCC3000 Research Report
3 units | Core
05

Admission Requirements

a) Candidates admitted to the programme must be holders of the Uganda Advanced Certificate of Education (UACE) or its equivalent, with at least two principal passes in the relevant subjects.

b) Holders of relevant Diplomas in related subjects from Kampala International University or other recognized institution will be eligible for admission to the degree course.

06

Fees and Application Guidance

Tuition, functional fees and any programme-specific charges are confirmed by KIU Admissions and Finance for each intake. Applicants should review the current fee schedule before submitting an application.