| Unit name | Data Analytics |
|---|---|
| Unit code | ECONM0031 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Crespo |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Economics |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
This unit is taught in two sections. In the first part the essential ideas of mathematical statistics will be studied. The fundamental ideas of mathematical statistics were begun to be developed in Europe in the eighteenth century and now constitute a large discipline on their own. Understanding these fundamental ideas is essential for much of your later work. Econometrics, a subject which will be new to most of you, is introduced in the second part of the unit. Mathematical statistics is the foundation of Econometrics as well. Econometrics is the name given to methods developed by economists to analyse economic and financial relationships using empirical data. If Economics and/or Finance have a valid claim to be sciences, which use empirical observations to verify or falsify its theories and to predict future events, then Econometrics is how this is achieved. Hence, Econometrics combines ideas from both Statistics and Economics and Finance.
How does this unit fit into your programme of study?
Whenever decisions in the economy are taken under uncertainty, then the fundamental statistical concepts of random variables, their distributions and the relationship between random variables become vital to understanding the decision-making process. Many modern theories in economics and finance and management build upon these ideas. Similarly, Econometric results are now used to support positions and policies in every part of modern society. Having some knowledge of the subject is essential if you are going to be able to understand what these results really mean. You may also find that you will want to use it in your dissertation.
An overview of content
The aim of this unit is to teach some basic statistic and econometric methods in the context of real-world empirical problems. The first part of the course concentrates on basic statistical techniques, which are required for the study of econometrics in the second part of the course. Although several key theoretical concepts are introduced, the emphasis is on applying statistical and econometric techniques to real-world problems in economics, finance and management.
How will students, personally, be different because of the unit?
The students will get an understanding of basic concepts in statistics, which are used in economic and financial theory and form a foundation of econometrics. Similarly, the unit will teach econometrics to students whose primarily interest is not in econometrics, but to apply econometric techniques to real-world empirical problems. The unit will enable students to use these techniques in their dissertation and to have a general understanding of published econometric results.
Learning Outcomes
At the end of the course a successful student will be able to:
Teaching will be delivered through a combination of synchronous and asynchronous sessions such as face-to face for large and small groups, online learning resources and interactive learning activities. Some classes will be held in computer labs in which students will be given data sets and structured problem-solving exercises to gain “hands-on” practice in using the relevant statistical package: students will complete these exercises in their own time.
How you will be assessed?
Tasks which help you learn and prepare you for summative tasks (formative):
The students will be asked to read an academic article and write a 1000-word essay based on their reading. This assignment is designed to examine the student’s ability to work with the concepts and techniques introduced in the course (ILO 1). In addition, five computer exercises will be covered during the term, which will enable students to apply statistic and econometric techniques to answer real-world empirical questions (ILOs 2 & 3) and to develop expertise in using the relevant statistical/econometrics computer package (ILO 4).
Tasks which count towards your unit mark (summative):
Coursework (100%) in two parts, consisting of a 1000-word essay, and questions relating to a dataset to estimate several models. Assesses ILOs 1-4
When assessment does not go to plan
When a student fails the unit and is eligible to resubmit, failed components will be reassessed on a like-for-like basis.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. ECONM0031).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
