Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title STATISTICS FOR ENVIRONMENTAL SCIENTISTS
Code ENVS222
Coordinator Dr M Spencer
Earth, Ocean and Ecological Sciences
M.Spencer@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2019-20 Level 5 FHEQ First Semester 15

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

(LO1) Make sense of the statistical terms that appear in scientific papers and the media

(LO2) Summarize data using graphs, tables, and numerical summaries

(LO3) Choose appropriate statistical methods to answer research questions

(LO4) Use statistical software to apply these methods, and interpret the output

(S1) Problem solving skills

(S2) Numeracy

(S3) IT skills

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 (hypothesis tests)

Workshop 3 t-tests in Minitab

Lecture 7 One-way analysis of variance

Lecture 8 Two-way analysis of variance

Workshop 4 Analysis of variance in Minitab Practical project (formative feedback)

Lecture 9 Correlation

Lecture 10 Regression

Workshop 5 Correlation and regression in Minitab

Lecture 11 General linear models

Lecture 12 Review of practical project and problem solving (general linear models)

Workshop 6 General linear models in Minitab

Lecture 13 Two-way tables

Lecture 14 Goodness of fit

Workshop 7 Categorical data analysis in Minitab

Lecture 15 Designing surveys and experiments

Lecture 16 Choosing analyses

Workshop 8 Designing studies and choosing analyses

Lecture 17 Nonparametric statistics

Workshop 9 Nonparametric statistics in Minitab

Lecture 18 Revision

Lecture 19 Assignment feedback

Workshop 10 Revision

Teaching and Learning Strategies

Teaching Method 1 - Lecture Description: Lectures provide theoretical background Teaching Method 2 - Other Description: data collection and analysis

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 19

         28

 47
Timetable (if known)              
Private Study 103
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 1  120 minutes.    80       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 1, week 11  Report of approx 2 p    20       

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.