Skip to main content

Unit information: Data Analytics in 2021/22

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Data Analytics
Unit code EFIMM0104
Credit points 15
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Crespo
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

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 a number of key theoretical concepts are introduced, the emphasis is on applying statistical and econometric techniques to real-world problems in economics, finance and management.

Unit aims:

(1) To give students an understanding of basic concepts in statistics, which are used in economic and financial theory and form a foundation of econometrics.

(2) To 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.

Intended Learning Outcomes

At the end of the course a successful student will be able to:

  1. interpret and analyse fundamental ideas in statistics such as frequency distributions, quantitative/qualitative data graphs, descriptive statistics, correlation, estimation, and hypothesis testing.
  2. use simple estimation and hypothesis testing procedures in econometrics, and to recognise econometric results techniques to analyse and test economic hypotheses.
  3. be proficient in the application of different data analysis techniques in order to use them in their future academic or professional career.
  4. apply the relevant statistical/econometrics computer package to estimate regressions in the context of real-world economic problems.

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions such as online teaching for large and small group, face-to-face small group classes (where possible) and interactive learning activities

Assessment Information

Coursework (85%) and MCQ Test (15%).

Resources

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. EFIMM0104).

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 Faculty workload statement relating to this unit for more information.

Assessment
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. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

Feedback