Bachelor’s Degree in Quantitative and Statistical Methods Applied to Management

Mode of Study

Online classes, interactive LMS, and on-site workshops

Intake

29th January 2026

Duration

1 year top up available, 3 Years

Free offered

Payments

Registration Fee :

Rs.32030

Course Fee :

Top-Up : Rs.383000

3 Years : 620000

Programme Overview

The Bachelor’s Degree in Quantitative and Statistical Methods Applied to Management is designed to train professionals capable of using mathematical, statistical, and computational tools to analyze economic, financial, and managerial data in support of evidence-based decision-making in public and private organizations.

The programme combines management sciences, applied mathematics, statistics, and data analysis technologies, preparing graduates to operate effectively in data-driven business, economic, and institutional environments.

The curriculum is structured in accordance with the LMD (Licence–Master–Doctorate) system and aligned with international higher education and ECTS-equivalent standards.

Programme Objectives

The programme aims to:

Develop strong mastery of quantitative and statistical methods applied to management
Train students to collect, process, analyze, and interpret data
Build proficiency in statistical and data analysis software such as
SPSS, R, Python, Excel, and Power BI
Enable students to conduct economic studies and quantitative research
Prepare analysts capable of integrating research outcomes into managerial decision-making

Programme Structure

Duration: 3 Years (6 Semesters)
Academic System: LMD
Total Credits: 180 ECTS
Field: Economics and Management
Specialization: Quantitative and Statistical Methods

Year 1 – Foundations in Management and Mathematics (60 Credits)

Core Courses (48 Credits)

Code	Course Title	Credits
MQS 101	Introduction to Management and Economics	6
MQS 102	General Mathematics I (Algebra and Analysis)	6
MQS 103	Descriptive Statistics	6
MQS 104	Basic Computing and Spreadsheets (Excel, SPSS)	6
MQS 105	Microeconomics	6
MQS 106	General Accounting	6
MQS 107	University Methodology and Academic Communication	6
MQS 108	Financial Mathematics	6

Optional Courses (Choose two – 12 Credits)

Code	Course Title	Credits
MQS 109	Introduction to Programming (Python / R)	6
MQS 110	English for Economics and Statistics	6
MQS 111	Scientific Writing and Presentation Techniques	6
MQS 112	Law and Economic Institutions	6

Year 2 – Quantitative Methods Applied to Management (60 Credits)

Core Courses (48 Credits)

Code	Course Title	Credits
MQS 201	Inferential Statistics	6
MQS 202	General Mathematics II (Linear Algebra & Differential Calculus)	6
MQS 203	Probability and Modeling	6
MQS 204	Econometric Methods I	6
MQS 205	Data Analysis (SPSS / Advanced Excel)	6
MQS 206	Game Theory and Decision Making	6
MQS 207	Research Methodology and Observation Internship	6
MQS 208	Information Technology Applied to Management (Statistical Software)	6

Optional Courses (Choose two – 12 Credits)

Code	Course Title	Credits
MQS 209	Social and Demographic Statistics	6
MQS 210	Introduction to Data Science	6
MQS 211	Simulation and Mathematical Modeling	6
MQS 212	Advanced Regression Analysis	6

Year 3 – Professional Applications and Advanced Analysis (60 Credits)

Code	Course Title	Credits
MQS 301	Advanced Econometrics and Time Series Analysis	6
MQS 302	Multivariate Analysis	6
MQS 303	Operations Research and Optimization	6
MQS 304	Statistics for Decision Making	6
MQS 305	Data Science Applied to Management (Python / R / Power BI)	6
MQS 306	Professional Dissertation / Final Year Project	12
MQS 307	Professional Internship (Minimum 3 Months)	12
Total		60

Overall Credit Allocation

Academic Year	Focus Area	Credits
Year 1	Mathematical, statistical, and economic foundations	60
Year 2	Quantitative methods and data analysis	60
Year 3	Professional applications and data science	60
Total	Full Programme (LMD)	180 ECTS

Learning Outcomes and Skills Acquired

Graduates of the programme will be able to:

Apply quantitative and statistical methods to management and research problems
Use statistical software and programming tools for data analysis
Design decision-support and optimization models
Conduct economic, financial, and managerial studies
Produce professional analytical reports and academic research outputs

Career Opportunities

Graduates may pursue careers as:

Statistician / Data Analyst
Quantitative Economist
Management or Performance Analyst
Economic Studies and Evaluation Officer
Management Information Systems (MIS) Officer
Research, Planning, and Policy Consultant

Progression and Further Studies

The degree provides access to:

Master’s Degrees in Economics, Management, or Statistics
Master’s Degrees in Data Analytics, Business Analytics, or Econometrics
MBA programmes with quantitative or analytics specialization
Research-oriented postgraduate programmes
(subject to admission requirements)

Academic Note

This programme is structured in compliance with the LMD academic framework and an ECTS-aligned credit system, ensuring academic rigor, transparency, and international comparability.

Frequently Asked Questions

Email: [email protected] Phone: +94 777-29-90-91

Yes. Degrees are awarded by globally recognized universities and can be verified through our official verification process.

Yes. We have certified training centers including SITC, MIBA, ISBM, and HDI CAMPUS II. You may visit the nearest one for support.

Once reviewed, you’ll receive a formal welcome email from the awarding university and an offer letter from HDI CAMPUS.

Yes. The degrees we offer are awarded by universities recognized by the University Grants Commission (UGC) of Sri Lanka.

Yes. This degree is accepted as a valid qualification for employment in both the government and private sectors in Sri Lanka. It can also be used to meet the eligibility requirements for promotions within those sectors.

This is a Blended Learning program, which combines both online and on-site components. All lectures are delivered online via Zoom, ensuring accessibility and flexibility for students. In addition, each subject includes relevant practical workshops and training sessions to enhance hands-on learning and real-world application.

Evaluation is carried out through a combination of the following methods:

Continuous Assessments: Assignments, quizzes, and practical activities throughout the course.
Written Examinations: Conducted at the end of each module or semester.
Project Work / Research Component: Depending on the program, students may be required to complete a project or research-based assignment.

You can pay the balance:

In full
In 3, 6, or 12 installments
Payments can be made via bank deposit or online transfer.

HDI CAMPUS Fee: Rs. 10,000/-
University Registration Fee: $72 (Approx. Rs. 22,030/-)

Once the initial registration fee is fully paid, the remaining balance can be settled either as a lump sum or through an installment plan of 3, 6, or 12 payments.

You will receive LMS credentials after your registration is complete. All your lecture materials, assignments, and progress tracking are available there.

Certified copies of academic certificates
Passport-size photo
NIC / Passport copy
English proficiency proof (if applicable)
CV (For Master’s/PhD)
Research proposal (For PhD)

For guidance and support, please contact:
[email protected]

Bachelor: Typically within the final semester.
Master: Typically within 6 to 12 months.
PhD: Typically within 18 to 24 months.

Yes. All students — Bachelor, Master, and PhD — must successfully defend their thesis/project in a formal Viva Test. You will present your research and answer questions from an academic panel.

Selected Master and PhD theses will be published in the HDI CAMPUS Publication Portal and/or Academic Journal.
This allows your research to contribute to global academic knowledge and gives you a published academic record.

Yes, HDI CAMPUS facilitates publication in its partnered Academic Journal (www.acadj.org) with minimal fees. You may also publish in other approved journals.

Bachelor: Not mandatory, but encouraged.
Master: Not mandatory, but encouraged.
PhD: Yes, you are required to publish at least 2 articles in indexed journals. The university facilitates low-cost publication in Academic Journal (www.acadj.org).

The acceptable similarity index is below 20% (excluding references, tables, and appendices). All theses will be checked using a plagiarism detection system.

You may request a change in topic by submitting a formal request to the Faculty Research Committee. Changes are subject to approval and must be made early in the research process.

After your thesis topic is approved, the university will assign a qualified academic supervisor who has expertise in your subject area. You will be notified of your supervisor by email.

Students are encouraged to propose their own thesis topics aligned with their academic interests. However, topics must be approved by the Faculty Research Committee. Supervisors will assist in refining topics.

Distance Learning University

HDI CAMPUS

Mode of Study

Intake

Duration

Free offered

Payments

Programme Overview

Programme Objectives

Programme Structure

Year 1 – Foundations in Management and Mathematics (60 Credits)

Core Courses (48 Credits)

Optional Courses (Choose two – 12 Credits)

Year 2 – Quantitative Methods Applied to Management (60 Credits)

Core Courses (48 Credits)

Optional Courses (Choose two – 12 Credits)

Year 3 – Professional Applications and Advanced Analysis (60 Credits)

Overall Credit Allocation

Learning Outcomes and Skills Acquired

Career Opportunities

Progression and Further Studies

Academic Note

Frequently Asked Questions

Distance Learning University

HDI CAMPUS

SITC BRANCH

Main StreetRathnapura

ISBM BRANCH

Colombo StreetKegalle

MIBA BRANCH

Nuwaraeliya RoadPussellawa

HDI CAMPUS II

PelmadullaRathnapura

SITC BRANCH II

DoranuwaRuwanwelle

LMS : www.hdic.edu.lk

ADMINISTRATION

05, Rajapihilla Mawatha, Kandy

Administration | 0817630200

[email protected]

Main Street
Rathnapura

Colombo Street
Kegalle

Nuwaraeliya Road
Pussellawa

Pelmadulla
Rathnapura

Doranuwa
Ruwanwelle

05, Rajapihilla Mawatha,
Kandy