Studying at York
Quantitative Methods - ECO00022C
- Department: Economics and Related Studies
- Credit value: 20 credits
- Credit level: C
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
Module summary
This module will provide the grounding in mathematics and statistics that is essential for progression onto further economics courses, and more generally for any form of empirical work in economics, business, or social sciences.
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 2 2023-24 |
Module aims
1. To introduce some of the ways in which mathematics is used in the study of economics, and to ensure sufficient grounding for the mathematical aspects of core economics modules in later stages of the degree.
2. To introduce techniques of statistical inference that are routinely used in solving problems in economics, business, and other social sciences. Students will be provided with a foundation for intermediate econometric and statistical modules offered in later stages of the degree.
Module learning outcomes
Familiarity with the main mathematical techniques used in economics, including a review of algebra, sequences and series, differential and integral calculus, partial differentiation and constrained optimisation.
Working understanding of statistical concepts of populations, samples and sampling distributions; the ability to describe and apply procedures for estimating quantities of interest and testing claims about such quantities; the ability to describe the role of correlation and simple regression in analysing the relationship between two variables, and apply these tools and discuss empirical results.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 80 |
| Online Exam -less than 24hrs (Centrally scheduled) | 20 |
Special assessment rules
None
Additional assessment information
Self marking exercises will be available; answers will be provided to the problem sets and gone through carefully in seminars; example questions in lectures.
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 80 |
Module feedback
They will get answers to the problem sets in the seminars that will provide content for the quizzes. They will get feedback via their scores in the quizzes. They will be able to ask in seminars / office hours if they don’t understand an answer. Quiz questions will resemble the questions in the final exam.
Indicative reading
Geoff Renshaw; Maths for Economics, Oxford University Press
John Freund's mathematical statistics with applications
One of the many A level mathematics text books (e.g. Crawshaw and Chambers, Advanced Level Statistics)