Module Code - Title:
EC4023
-
QUANTITATIVE METHODS FOR ECONOMICS
Year Last Offered:
2025/6
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
The aim of the module is to introduce a range of basic quantitative skills, concepts and techniques widely used in modern applied work in economics. One of the most important roles of economics is to rigorously identify and quantify economic relationships. Accordingly, this course shows students how to analyse data using quantitative and graphical techniques, and to interpret the results appropriately. This includes the formulation and technical specification of research design, statistical software, results generation and interpretation. Students will acquire comprehensive knowledge and experience of conducting data analysis using statistical software.
Syllabus:
This module covers a range of fundamental quantitative tools that are relevant to applied economics. The course begins with a review of mathematical functions and equations. This is followed by studying the rules of differentiation and optimization applied to economic problems. Additionally, the module will deal with descriptive statistics, data charts and plots; and also will introduce statistical tools, including sampling methods, hypothesis testing and simple linear regression.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to
- investigate social and economic issues using statistical software and simple data analysis techniques.
- demonstrate their understanding of common mathematical concepts used in economic modelling including functions, derivatives, and optimisation.
- interpret basic statistical tests used in scientific publications.
Affective (Attitudes and Values)
On successful completion of this module, students will be able to
- critically question statistical results and their graphical representations.
- demonstrate awareness of the relationship between economic theory, statistical theory and practice, and observed data.
Psychomotor (Physical Skills)
How the Module will be Taught and what will be the Learning Experiences of the Students:
This module will be taught through traditional lectures and supervised laboratory sessions where students will be equipped with the tools of economic analysis for the purpose of undertaking research into economic issues. The module also contains a substantial amount of self-study and group work. Continuous self-study and active group participation are essential to learning to apply the statistical and mathematical concepts covered in the module using scientific software.
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
Irizarry R. (2023)
Introduction to Data Science: Data Analysis and Prediction Algorithms with R
, CRC Press
Illowsky, B. and S. Dean (2022)
Introductory Statistics
, OpenStatX
Other Relevant Texts:
Chiang, A.C. and K Wainwright (2015)
Fundamental Methods of Mathematical Economics
, McGraw-Hill
Weiss, N.A. (2015)
Introductory Statistics
, Pearson
Programme(s) in which this Module is Offered:
BAULARUFA - ARTS
Semester(s) Module is Offered:
Autumn
Module Leader:
lukas.kuld@ul.ie