Syllabus

Data collection and data quality

Code
ST3012
Points
7.5 ECTS-credits
Level
Second Cycle Level 1
School
School of Information and Engineering
Subject field
Statistics (STA)
Group of Subjects
Statistics
Disciplinary Domain
Natural Science, 100%
This course can be included in the following main field(s) of study
Microdata Analysis1
Progression indicator within (each) main field of study
1A1N
Approved
Approved by the Faculty School of Information and Engineering, 26 October 2010.
This syllabus is valid from 01 November 2010.
Revised
Revised, 18 December 2012.
Revision is valid from 31 December 2012.
Discontinued
22 December 2021
Download as pdf To course page

Learning Outcomes

On completion of the course students will be able to

· describe and understand the importance of various types of data and various forms of data collection,
· use and evaluate various types of data and various types of data collection,
·  identify important factors which contribute to data quality and data collection quality,
· develop and evaluate a new data collection system,
·  ensure that data collection can be replicated in another context,
· critically analyze the importance of meta data,
· describe and understand the significance of laws which regulate data storage.

Course Content

The course considers various types of data as well as various forms of data collection, for example the collection of data over time, demographic data collected by means of different types of sensors, selection analysis and experimentation.
Throughout the course the laws regulating data collection, strategies which can be used for better data collection and data quality, and the connection between the collection and storage of data will be analyzed.

Assessment

The course is examined through an individual project, preparation and reporting, 3 credits (U-G), laboratory reports, 2 credits (U-G) and individual assignments, 2.5 credits (U-VG). A prerequisite for grading is that students actively participate in at least two thirds of timetable lectures, workshops and meetings.

Forms of Study

Lectures, laboratory work, project work and seminars.

Grades

The Swedish grades U–VG.

The final grade for the course is based on an overall assessment by the examiner.

Prerequisites

  • Bachelor degrree (Statistics, Informatic, Computer Science or equivalent) including following courses
  • Database management, 7,5 credits or equivalent knowledge
  • Data Analysis and Statistics I 7,5 credits or equivalent knowledge
  • Object Oriented Programming, 7,5 credits First Cycle

Other Information

A maximum of five examinations possible.

Literature

  • Aktuella forsknings- och nyhetsartiklar inom området.
    Other: 200 sidor
  • Sapsford, R., Jupp, V.. (2006) Data collection and analysis. 2 ed. London : SAGE Publications in association with the Open University. (332 p). ISBN 978-0-7619-4362-4