MT2SWCNU-Statistics for Weather and Climate

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:
Co-requisites:
Modules excluded: MTMG06 Statistics for Weather and Climate Science
Current from: 2020/1

Module Convenor: Prof Ted Shepherd

Email: theodore.shepherd@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.

The Module lead at NUIST is Dr Getachew Dubache (gechdubache@yahoo.com).

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 analyze data and draw correct  inferences;


• Use statistical software.

Additional outcomes:

• Discuss the development and importance of  statistics;

• Appraise and criticize 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 python modules to analyze and interpret data.

Brief description of teaching and learning methods:

Lectures and computer practical classes with python

 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		16
Practicals classes and workshops		32
Guided independent study:		52
Total hours by term	0		0
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 Convenor 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):

Last updated: 15 July 2020