The course introduces students to the methods of quantitative economics, i.e. to how data are used in economics. Beginning from an elementary level (assuming no background in statistics), the course shows how economic data can be described and analysed. The elements of probability and random variables are introduced in the context of economic applications. The probability theory enables an introduction to elementary statistical inference: parameter estimation, confidence intervals and hypothesis tests. With these foundations, students are then introduced to the linear regression model that forms a starting point for econometrics. Throughout the course the emphasis is on the practical application of economic analysis from an empirical perspective.
The main objective of EC114 is to enhance students' knowledge and conceptual understanding of the treatment of data in economics. Upon completion of the course, each student will be aware of the main sources of economic data; how to construct and interpret graphs of the data; how to construct summary statistics. Students will have acquired a knowledge of the statistical methods needed for the analysis of economic issues. In particular, students' will have learned how to interpret the estimates of simple economic models and to conduct tests of hypotheses about the model's parameters.
The module provides the students with a wide set of tools which will prove to be particularly relevant during their working careers. Their ability to read, understand and properly manipulate data will be strongly enhanced, from both a theoretical and empirical point of view. Students are introduced to the knowledge of widely used statistical computational packages and plenty of examples from real datasets will reinforce student's control of the most important statistical techniques.
The main objective of EC114 is to enhance students' knowledge and conceptual understanding of the treatment of data in economics. Upon completion of the course, each student will be aware of the main sources of economic data; how to construct and interpret graphs of the data; how to construct summary statistics. Students will have acquired a knowledge of the statistical methods needed for the analysis of economic issues. In particular, students' will have learned how to interpret the estimates of simple economic models and to conduct tests of hypotheses about the model's parameters.
The module provides the students with a wide set of tools which will prove to be particularly relevant during their working careers. Their ability to read, understand and properly manipulate data will be strongly enhanced, from both a theoretical and empirical point of view. Students are introduced to the knowledge of widely used statistical computational packages and plenty of examples from real datasets will reinforce student's control of the most important statistical techniques.
- Module Supervisor: Quentin Lippmann
- Module Supervisor: Eric Smith