Module Catalogues, Xi'an Jiaotong-Liverpool University   
 
Module Code: ENV203
Module Title: Statistics for Environmental Scientists
Module Level: Level 2
Module Credits: 5.00
Academic Year: 2017/18
Semester: SEM1
Originating Department: Environmental Science
Pre-requisites: N/A
   
Aims
This module provides training in statistics for environmental scientists. We emphasize the use of software to analyze real environmental data. We do not assume extensive prior knowledge. We will teach the essential theory alongside the practical components.
Learning outcomes 
By the end of this module students will be able to:

1. make sense of the statistical terms that appear in scientific papers and the media

2. summarize data using graphs, tables, and numerical summaries

3. choose appropriate statistical methods to answer research questions

4. use statistical software to apply these methods, and interpret the output

Method of teaching and learning 
Lectures will provide background on the theory. Workshops and problem sessions will give practical experience in data analysis. Feedback will be given on these sessions, for example through peer marking. Individual and group projects will use all the skills taught in lectures and workshops.
Syllabus 
Lecture 1 Graphical and numerical summaries of data

Lecture 2 Probability and the normal distribution

Workshop 1 Descriptive statistics and probability distributions

Lecture 3 Samples, populations and the Central Limit Theorem

Lecture 4 Confidence intervals

Workshop 2 Calculating and interpreting confidence intervals

Lecture 5 Hypothesis tests

Lecture 6 Problem solving

Workshop 3 t-tests in SPSS

Lecture 7 One-way analysis of variance

Lecture 8 Two-way analysis of variance

Workshop 4 Analysis of variance in SPSS

Lecture 9 Correlation

Lecture 10 Regression

Workshop 5 Correlation and regression in SPSS

Lecture 11 General linear models

Lecture 12 Problem solving

Workshop 6 General linear models in SPSS

Lecture 13 Two-way tables

Lecture 14 Goodness of fit

Workshop 7 Categorical data analysis in SPSS

Lecture 15 Designing surveys and experiments

Lecture 16 Choosing analyses

Workshop 8 Designing studies and choosing analyses

Lecture 17 Practice exam questions
Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester 26       14    110  150 

Assessment

Sequence Method % of Final Mark
1 Computer Based Exam 60.00
2 Individual Report On Data Analysis Problem 20.00
3 Individual Report On Data Analysis Problem 20.00

Module Catalogue generated from SITS CUT-OFF: 10/22/2017 9:34:34 PM