Syllabus for Statistics and Data Analysis Methods

Statistik och dataanalysmetoder

A revised version of the syllabus is available.

Syllabus

  • 5 credits
  • Course code: 1HY013
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Earth Science A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2014-03-13
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2016-04-25
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 30, 2016
  • Entry requirements: 120 credits with at least 90 credits in Earth Sciences or 90 credits in Physics.
  • Responsible department: Department of Earth Sciences

Learning outcomes

After the completion of the course, the student should be able to

  • Explain basic statistical terms and concepts
  • Identify statistical methods that are suitable for exploring, describing and analysing earth science data
  • Summarise and visualise earth science data with computing software
  • Compare, relate and predict hydrological and geographical data in time and space

Content

The course introduces basic concepts in descriptive and inferential statistics, as well as data exploration methods, with specific focus on their use in hydrology and physical geography. Topics covered include probability distributions, data transformations, confidence intervals, hypothesis testing, frequency analysis, correlation, regression and time series analysis.

Instruction

Lectures and exercises.

Assessment

Assessment is divided between a written exam (2 credits ) and exercises (3 credits)

Reading list

Reading list

Applies from: week 35, 2016

Some titles may be available electronically through the University library.

  • McKillup, Steve; Dyar, M. Darby Geostatistics explained : an introductory guide for earth scientists

    Cambridge, UK: Cambridge University Press, 2010

    Find in the library

    Mandatory

  • Lane, D.M. Online Statistics Education: A Multimedia Course of Study, v. 2.0.

    onlinestatbook.com,

    Recommended reading, not obligatory

  • Diggle, Peter.; Chetwynd, Amanda. Statistics and scientific method : an introduction for students and researchers

    Oxford: Oxford University Press, 2011.

    Recommended reading, not obligatory

    Find in the library

  • Harris, Richard; Jarvis, Claire Statistics in geography and environmental science

    Abingdon, Oxon: Routledge, 2013

    Recommended reading, not obligatory

    Find in the library