AERD30200 Statistics and Econometrics

Academic Year 2021/2022

The aim of this module is to introduce students to the analysis of economic data using statistics and econometrics. The module builds and extends on prior statistics knowledge. Statistical and econometric methods are applied to learn from economic data about relationships, causes and effects. The module starts with adopting standard statistical concepts and continues with different econometric regression models, discusses common problems when estimating such models and explains how to interpret the estimates from the models. The course has an applied focus and students will get hands-on experience with analysing actual survey and economic data by applying statistical and econometric methods.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module, you should be able to apply statistical concepts and econometric models and interpret the results. Specifically, you should be able to:

• select the appropriate among a set of statistical approaches, apply it to a data set and interpret its results
• explain the meaning and purpose of econometric analysis
• understand concepts and assumptions of the linear regression model
• critically evaluate linear and non-linear regression models and discuss potential problems
• estimate and interpret statistics using the computer software SPSS

Indicative Module Content:

• Surveys, samples and data
• Descriptive statistics and visualizations for single variables and relationships between variables
• Inferential statistics including hypothesis test and confidence intervals
• Linear regression with one variable
• Linear regression with multiple variables
• Non-linear regression (polynomial, logarithmic, interaction effects)

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities

12

Autonomous Student Learning

60

Lectures

18

Computer Aided Lab

18

Total

108

Approaches to Teaching and Learning:
The approach to teaching and learning is based on lectures, active learning and hands-on, computer-based work. 
Requirements, Exclusions and Recommendations
Learning Requirements:

This module will build on the material covered in an “Introduction to Statistics” course, such as Applied Biostatistics (FOR20100).


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Group Project: Group Project Report & Presentation Coursework (End of Trimester) n/a Standard conversion grade scale 40% No

60

Continuous Assessment: Continuous assessments Throughout the Trimester n/a Standard conversion grade scale 40% No

40


Carry forward of passed components
No
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Solutions to assessments will be discussed interactively in class after the assessment.

Stock, J. and Watson. M (2014). "Introduction to Econometrics", updated 3rd edition, Pearson Education.
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Autumn
     
Lecture Offering 1 Week(s) - Autumn: All Weeks Wed 09:00 - 10:50
Computer Aided Lab Offering 1 Week(s) - Autumn: All Weeks Wed 15:00 - 16:50
Autumn