MTMC01-Foundations of Statistical Inference

Module Provider: Meteorology
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded: MTMG06 Statistics for Weather and Climate Science or MT2SWC Statistics for Weather and Climate Science
Current from: 2023/4

Module Convenor: Prof Ted Shepherd
Email: theodore.shepherd@reading.ac.uk

Module Co-convenor: Dr Ben Harvey
Email: b.j.harvey@reading.ac.uk

Type of module:

Summary module description:

A module comprising both a lecture and a practical component, which together introduce students to the use of statistical methods in climate science, and their practical application.

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 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:

• Introduction to statistics: basic concepts, history


• Exploratory data analysis: summary statistics


• Forecast verification: skill scores


• Linear regression: correlation


• Multiple regression: confounders, causality


• Time series analysis: autocorrelation


• Concepts of probability: Bayes theorem


• Probability distributions


• Parameter estimation: confidence intervals


• Hypothesis testing: significance tests, p-values

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.