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MT2SWC - Statistics for Weather and Climate Science

MT2SWC-Statistics for Weather and Climate Science

Module Provider: Meteorology
Number of credits: 10 [5 ECTS credits]
Level:5
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites: A Level Maths
Co-requisites:
Modules excluded: MTMG06 Statistics for Weather and Climate Science
Current from: 2019/0

Module Convenor: Dr Rob Thompson

Email: robert.thompson@reading.ac.uk

Type of module:

Summary module description:
This module introduces the basic statistical concepts and reasoning as required for robust environmental science, providing experience of using statistical methods in the right contexts and demonstrating the correct use of which technique to allow critical interpretation of weather and climate data.

Aims:
This module aims to introduce basic statistical concepts and reasoning relevant to environmental science, as well as provide experience in the proper use of statistical methods for the analysis of weather and climate data.

Assessable learning outcomes:

By the end of this module the student should be able to:



• Describe the main concepts in statistical science;



• Select and compare appropriate analysis methods;



• Critically analyse data and draw correct inferences;



• Use statistical software.


Additional outcomes:

• Discuss the development and importance of statistics;



• Appraise and criticise quoted statistics (transferable skill).


Outline content:

The lecture content covers:



• History of statistics;



• Exploratory data analysis;



• Probability distributions;



• Statistical inference;



• Linear modelling;



• Multivariate methods;



• Time series analysis.



The practical content involves supervised hands-on experience using statistical software to analyse and interpret data.


Brief description of teaching and learning methods:
Lectures and computer practicals.
Reading:
Wilks, D.S., 1995: Statistical methods in the Atmospheric Sciences. Academic Press.
Storch, H. and Zwiers, F.W., 1999: Statistical analysis in climate research. Cambridge University Press.

Contact hours:
  Autumn Spring Summer
Lectures 10
Practicals classes and workshops 20
Guided independent study: 70
       
Total hours by term 100
       
Total hours for module 100

Summative Assessment Methods:
Method Percentage
Written assignment including essay 100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:
Essay assignment and practical assignments.

Formative assessment methods:

Penalties for late submission:
The Module Convener will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

  • The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
    You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

    Assessment requirements for a pass:

    40%.


    Reassessment arrangements:

    Resit examination.


    Additional Costs (specified where applicable):
    1) Required text books:
    2) Specialist equipment or materials:
    3) Specialist clothing, footwear or headgear:
    4) Printing and binding:
    5) Computers and devices with a particular specification:
    6) Travel, accommodation and subsistence:

    Last updated: 8 April 2019

    THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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