Undergraduate

modules

Modules

ECO1009 : Analysing Economic Data

Semesters
Semester 2 Credit Value: 10
ECTS Credits: 5.0

Aims

To develop an understanding of estimation and inference as a foundation for applied economics.

Original Summary:
This module is an introduction to statistics and date manipulation for economists and disciplines related to economics. The course considers the basics of data analysis, how do we explore and analyse data. We use a variety of statistical methods to investigate and interpret real world data. The module will also include an introduction to analytical software.

Outline Of Syllabus

Graphical analysis
Correlation
Simple regression
Interpretation
An introduction to Stata

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture141:0014:00N/A
Guided Independent StudyAssessment preparation and completion140:0040:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching51:005:00N/A
Guided Independent StudyIndependent study141:0041:00N/A
Total100:00
Jointly Taught With
Code Title
ECO1007Statistical Methods for Economics
Teaching Rationale And Relationship

Lectures deliver main concepts
Seminars and workshops give the opportunity to work through example problems

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Written Examination602A70N/A
Exam Pairings
Module Code Module Title Semester Comment
ECO1007Statistical Methods for Economics2N/A
Exam Pairing Resits
Module Code Module Title Comment
ECO1007Statistical Methods for EconomicsN/A
Other Assessment
Description Semester When Set Percentage Comment
Report2M30Group Project - 2000 words
Formative Assessments
Description Semester When Set Comment
Prob solv exercises1MIn class test
Assessment Rationale And Relationship

Exam ensures learning of theoretical methods
Group project demonstrates that students can analyse and interpret real world data.

Reading Lists

Timetable