BIMWA12-Quantitative Methods
Module Provider: School of Biological Sciences
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Module version for: 2017/8
Module Convenor: Dr Tom Oliver
Email: t.oliver@reading.ac.uk
Summary module description:
Aims:
This module aims to introduce students to a range of statistical procedures commonly used in the analysis of data in the life sciences. In addition to indicating which tests to use in which circumstances, the module will also focus on the underlying assumptions associated with different procedures and how these should be verified. Students will also be instructed on the appropriate approaches to summarising and presenting the results of these statistical methods, including the use of graphs. Two statistical software packages will be used throughout: SPSS and MINITAB.
Assessable learning outcomes:
Assessable outcomes
On completion of this module it is expected that the students will have acquired an understanding of:
•the role of statistics in wildlife management and conservation
•the use a range of common univariate statistical tests with a single predictor variable but which vary in relation to: (i) the number of groups of data being analysed; (ii) whether the data are normally distributed or not; and (iii) whether the data are independent or not
•the critical assumptions associated with parametric tests, and how to test to ensure that data conform to these assumptions
•the use of transformations to manipulate data so that parametric tests can be used preferentially
•use of general linear models for analysing data where the response variable is measured on a continuous scale and there are several predictor variables, including use of interaction terms
•the use binary logistic regression for the analysis of data where the response variable is binary (e.g. present/absent, alive/dead) and there are several predictor variables, including use of interaction terms
•the use of stochastic and deterministic models in wildlife management and conservation, particularly in the context of population viability analysis
•the use of power analysis, and how it can be used to (i) plan scientific studies, (ii) limit the use of animals in scientific studies and (iii) be applied to presenting the results of “non-significant” results
•the correct approach for presenting and summarising the statistical methodologies discussed
•the use of both SPSS and MINITAB statistical software
Additional outcomes:
•An appreciation of the importance of good data management practices
•The relative merits of different software packages
Outline content:
The first half of the module will focus on basic statistical procedures where there is a single independent (predictor) variable. Tests to be discussed will include: one-sample t test, independent-sample t test; paired-sample t test; Mann-Whitney test; Wilcoxon matched-pairs test; one-way ANOVA; repeated-measures ANOVA; Kruskal-Wallis test; and Friedman test. These tests will be discussed in the context of: the number of groups of data being analysed; whether the data are normally distributed or not; and whether the data are independent or not. Additional sessions will cover: (i) the key assumptions associated with these tests (e.g. normality, homogeneity of variances); (ii) how these assumptions can be verified; and (iii) how data transformations can be used to manipulate non-normally distributed data so that parametric tests can be used. Consideration will be given to the use of degrees of freedom as a method to identify how statistical methods have been applied.
Students will then be given an introduction to general linear models: a parametric test in which several independent (predictor) variables are quantified in relation to a single independent (response) variable measured on a continuous scale. Topics that will be discussed include: degrees of freedom; sequential versus adjusted sums of squares, fixed versus random factors, and interaction terms.
At the end of the autumn term, students will be given a continuous assessment exercise consisting of a data analysis and presentation exercise: students will be given a set of data which they will be asked to analyse using several different techniques and to present the results of these analyses in an appropriate format. The last few weeks of the module will be set aside for students to complete this assessment in the presence of the module convenor, who will be able to offer guidance where necessary.
In the spring term, students will be introduced to a range of further statistical techniques commonly used in wildlife management and conservation. Particular attention will be given to binary logistic regression analysis, which enables investigators to quantify the importance of one or more predictor variables on a dependent (response) variable which is measured on a binary scale. In conservation, this is often used in models to investigate factors affecting the presence / absence of a species at particular locations. In addition, the module will cover topics such as mathematical modelling and power analysis, the latter being especially relevant to both minimising the use of animals in what can potentially be harmful studies and designing studies to demonstrate robust non-significant results.
The last two weeks of the spring term will be allocated to the continuous assessment component. This will be in the form of a FORMAL EXAMINATION. In Week 9 of the term, students will sit a mock exam to familiarise themselves with the work they are likely to encounter in the assessment itself. In Week 10, they will sit the formal exam itself.
Throughout the module students will be introduced to the most appropriate way to present results of these procedures as they would be expected to in e.g. a scientific paper or their research project thesis.
Brief description of teaching and learning methods:
Each session will typically be broken down into a 2h lecture and a 2h computer session. Each lecture will use a combination of an oral presentation and small-group exercises to illustrate one or more topics. The computer session will then provide students with the opportunity to apply and practice the techniques discussed in the lecture.
In the last few weeks of the autumn term, formal contact hours will be set aside to allow students to complete their continuous assessment work in the presence of the module convenor.
In the last few weeks of the spring term, formal contact hours will be set aside for the formal open-book examination assessment.
Summative Assessment Methods:
Method |
Percentage |
Written assignment including essay |
100 |
Other information on summative assessment:
Coursework: Students are expected to submit two pieces of coursework, one in each term. In the autumn term, this will be a data analysis and presentation exercise where students are given a set of data which they have to analyse using different techniques and to present the results of these analyses in an appropriate format. The last few weeks of the module will be set aside for students to complete this assessment in the presence of the module convenor, who will be able to offer guidance where necessary.
In the spring term, this will be a formal open-book examination in which students will be given a set of data which they will be asked to analyse using several different techniques and to present the results of these analyses in an appropriate format. The last two weeks of the module will be set aside for students to complete this assessment: Week 9 will consist of a mock exam; Week 10 will be devoted to the exam itself.
Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx
Requirements for a pass:
A mark of at least 50%
Reassessment arrangements:
Re-examination in August/September
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: 31 August 2017