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Unit information: Economic Data 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 Economic Data
Unit code EFIM10016
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Hans Sievertsen
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

This unit focuses on obtaining, processing and presenting economic data. The unit consists of three elements. First, students are introduced to the software packages MS Excel and R, including fundamentals in programming. Second, we discuss principles of good and poor data visualization practice with applications in R and MS Excel. Third, the students learn concepts that are important for understanding and presenting economic data in a non-misleading way, for example the definition of GDP, price-indices, survey weights and log-scales. The main software for the unit is R (which is freely available). Methods and solutions using MS Excel will also be shown.

Topics covered will include

  • How data is collected (e.g. issues with measurement error, missing values, survey weights).
  • Fundamentals of programming (e.g. object types, control structures, functions).
  • Principles of good and poor data visualization practice (e.g. the lie factor, data ink ratio)
  • Definitions of internationally used variables (e.g. GPD, Unemployment rates, consumer price index/inflation, Purchasing Power Parity).
  • Publicly available data sources from statistical agencies and international organizations.

The unit will draw on links that the department has with the Office for National Statistics.

Intended Learning Outcomes

Students will be able:

  • To obtain, process and describe data using verbal, numerical and visual methods;
  • To understand the conceptual issues in producing estimates of variables such as GDP, PPP or inflation;
  • To select appropriate visualization methods.
  • To select the appropriate software for a data task (i.e. spreadsheet software vs. programming software)
  • To create small programming scripts and create advanced graphs

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 project (100%) This assesses all learning outcomes

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. EFIM10016).

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.

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