Introduction to Statistics and Regression Analysis
Module Code: ECP77403
- ECTS Credit: 5
- Mandatory/Optional: Mandatory
- Period: Michaelmas term
- Module Personnel Lecturer: Professor Cian O'Shea
Module Learning Aims
This module provides an introduction to data analysis and statistical concepts relevant to economics. The focus of this module is on the practical application of quantitative reasoning, visualisation and data analysis. Students will be introduced to the necessary theory and tools for conducting their own independent statistical analyses. Topics covered in this module include descriptive measures, probability, measures of association, sampling and sample size estimation, and confidence intervals. Assignments and examples are based on real-world data and problems in a wide range of fields.
Module Content
Topics covered will include:
- Graphical and numerical data description
- Probability Theory
- Measures of Central Tendency
- The Central Limit Theorem
- Sampling and estimation
- Confidence Intervals
- Hypothesis Testing
- Introduction to classical linear regression
Module Learning Outcomes
On successful completion of this module, students should be able to:
- Explain and apply statistical terminology;
- Formulate problems in the language and terminology of statistics;
- Solve problems related to the topics in the module;
- Explain statistical reasoning in a clear, concise, and correct manner;
- Use statistical software to clean datasets and conduct basic descriptive data analysis.
Recommended Reading List
Primary Texts:
- J.M. Wooldridge, Introductory Econometrics: A Modern Approach, 7/e, Cengage, 2020
- Stock, J.H. and M.W. Watson. Introduction to Econometrics, Pearson (4e), 2019.
Secondary Reading
- Angrist, J.D. and Pischke, J. Mastering Metrics, Princeton University Press, 2015
- Huntington-Klein, N. The Effect, The Effect: An Introduction to Research Design and Causality, Routledge, 2021
Assessment Details
The module will be assessed through a mixture of continuously assessed coursework and the final project.
Module Website
Blackboard