BUU11530 Quantitative Methods for Business 2025/26

(10 ECTS)

Lecturer:

Lisa Biermann (semester 1), Bidush Nepal (semester 2)

Email: biermanl@tcd.ie
Office Hours: By appointment

Businesses rely on insights of managers and managers gain their insights by carefully and scientifically analysing data. This fundamental quantitative course aims to provide students with the necessary skills and techniques to be able to analyse data, make inferences and make better decisions. This module introduces students to essential quantitative techniques in mathematics and statistics that are fundamental for business decision-making.

It provides a foundation for solving practical business problems and making informed decisions based on data analysis. Practical exercises, case studies, and real-world applications are emphasized to ensure students can apply these quantitative methods confidently in professional environments. This module is essential for students aiming for careers in finance, economics, management, and related fields, where quantitative skills are crucial for success.

We aim to achieve the learning outcomes in this module over the two-semesters. This course will have a substantial hands-on nature i.e. we will be learning theoretical techniques as well as implementing them on real data. We will use Excel as a software of choice for this purpose. We will also, from time to time, discuss other relevant software and tools for such statistical analysis.

Learning and Teaching Approach

This module entails one 2-hour lecture block and 1 tutorial hour per week. 

The tutorials will run as a supplement to the content covered in lectures where we shall practice the problems and test the theories. We also intend to use the tutorial to brush up some fundamental mathematical concepts that may be required for successful completion of the module and program, in general.

The module intends to prepare the students for a career in business and management by providing them with tools and techniques to understand and analyse data. After successfully completing this module, students would be able to:

1. Appreciate the role of data driven insights generation in real world situations.
2. Understand and process unstructured data through descriptive and explorative mechanisms.
3. Understand and apply mathematical concepts and techniques in business scenarios.
4. Be able to use Excel for generating insights from real world datasets.
5. Critically analyse and use key statistical concepts in business settings.
6. Understand key challenges and limitations in data-driven decision making.

Workload

We would recommend the following core textbook for the course which will be broadly followed throughout the course.

• Statistics for Managers Using Microsoft Excel (global edition) – Levine, Stephan and Szabat, Pearson publishers.
• Jacques, Ian. Mathematics for economics and business. Pearson Education, 2006.

1. Essential Quantitative methods- Les Oakshott- Red Globe Press/Mcmillan International.
2. Lee and Peters. Business Statistics using Excel and SPSS, Sage Publishers, with STATLAB 1st Ed 2016.
3. Veal. Business Research Methods – a Managerial Approach, Pearson, multiple copies are available in the TCD Library.
4. Gujarati, Damodar N., and Dawn C. Porter. 2009. Basic Econometrics. New York: McGraw-Hill Irwin.

As supplemental training in Excel, we recommend to follow the LinkedIn Learning course Excel Essential Training (Office 365/Microsoft 365) by Dennis Taylor; to access, you may log on from lil.tcd.ie with your credentials and search for the course title.

Student Preparation for the Module

Attendance Policy

Students are expected to attend all the classes as well as tutorials for the module. Medical absences should be communicated to the instructors at earliest.

Preparation

Students should come to the class well prepared. You are expected to come to the class after reading any assigned material for the particular class. Students are also expected to spend sufficient time beyond class-hours (as indicated by course load for the module) to revise and prepare for the classes and assignments. 

COURSE COMMUNICATION

Please note that all course related email communication must be sent from your official TCD email address. Emails sent from other addresses will not be attended to.

The module will be assessed in three parts:

1. In-class exercises (40%)- There will be 4 in-class exercises in lectures mentioned below. These exercises will each carry a 10% weight for a total of 40 % weightage. The in-class assessments will take the form of quiz or in-class problem solving exercise. These will be individual in nature and will be solved and submitted in-class.
2. End of semester 1 Final Exam (30%) : There will be an exam at the end of semester 1 that will be comprised of subjective, conceptual and methodological questions. Students will be expected to use the techniques they learnt in class to suggest solutions. Students will also have to defend their choices of the methods based on the statistical theory taught. The end of semester 1 final exam will be of 2 hr duration. Additional information about the protocol for the exam will be provided closer to the due date.
3. End of semester 2 Final Exam (30%): There would be an end-term assessment that would be comprised of subjective, conceptual and methodological questions involving data about specific business purpose. Students would be expected to use the techniques they learnt in class to suggest solutions for the firm. End term assessment would expect students to use the techniques learnt in the second semester to be applied and insights derived from data. Students would also have to defend their choices of the methods based on the statistical theory taught. The end of semester 2 final exam would be of 2 hr duration. Additional information about the protocol for the exam would be provided closer to the due date.

Biographical Note: