Data Analysis in Ecology: Statistics for Ecologists & Field Biologists (10-week)
This tutor-led ecological statistics course provides a thorough introduction to the key statistical principles and methods used by ecologists and field biologists. It will appeal to a variety of practitioners in environmental science and management who want to improve their ability to display ecological data, and to use descriptive and inferential statistics to analyse the results from field surveys.
The course introduces students to the use of the following software: QED statistics and R. R is a free software environment for statistical computing, and can run on a wide variety of backgrounds; QED offers an easy to follow way of exploring a variety of statistical methods, with step-by-step calculations, and extensive built-in help. It is particularly useful for those with little prior mathematical knowledge. Please see below for IT Requirements.
As a part-time course taught online, Data Analysis in Ecology is ideal for professional ecological consultants, environmental managers and rangers, research and postgraduate students, and volunteers that are seeking flexible study combined with expert training. The course can be taken from anywhere in the world and is international in its use of case studies and examples. Past students on the Ecological Survey Techniques programme have joined us from the UK, the USA, Australia, Africa and Europe.
Data Analysis in Ecology aims to create a rich workshop experience by encouraging direct student and tutor interaction and discussion in an online setting.
This course can be taken with or without Masters-level credit; credit enables students to demonstrate their academic achievement and can count towards further postgraduate study. Students taking the course for credit submit an assessment of up to 2000 words or equivalent, students taking the course without credit will receive a Certificate of Attendance upon successful completion of the course.
The Ecological Survey Techniques Programme can help professionals to apply for Chartered Status (such as Chartered Environmentalist and Chartered Ecologist), and to meet relevant professional competency thresholds. Further information can be found in our Chartered status and essential skills guide.
Thinking of applying? Explore materials or revisit our online open event.
For first-hand accounts from Ecological Survey Techniques students please visit our student spotlights page.
The course tutor will guide students through a series of key topics via reading materials, online activities, and discussion forums. The discussion forums will be the primary space where students are able to interact with one another and their tutor to discuss questions, solve problems and share ideas - just as they would expect to do in a face-to-face classroom setting.
"I took this course as I've worked for several years now as a research technician in Zimbabwe and Zambia on lion, elephant and vulture projects. However, I have very little formal training and mostly learnt "on the job". I felt that this course would give me more confidence in analysing and presenting the data I collected."
A research technician on Data Analysis in Ecology
"Studying online is great for distance learning. The range of materials available online is staggering and this method is so different from my university experience many years ago"
Nsalambi, PGCert student
"I can say with full confidence that thanks to this course I finally understand stats and know how to do it myself!"
Karolina, PGCert student
Students will benefit from the expertise and practical experience of the course tutor throughout their time on the course, and will be able to receive advice and guidance tailored to the particular topic at hand. Students taking the course for credit will also benefit from individual feedback on their assessment submitted after the course.
Topics will be illustrated with worked examples and practical advice from the course tutor. Material will provide examples of how particular techniques have been applied to specific ecological investigations, giving full background and context to data sets for use in any calculation.
Learning materials are made available through the course Virtual Learning Environment ‘Moodle’, and reading is available to download or is accessible via the Bodleian Libraries'online library which provides an excellent range of e-books and e-journals. Students are required to purchase the core text Fowler et al (1998) Practical Statistics for Field Biology. Via their Oxford username, students can gain access to all the University’s electronic resources enabling them to conduct their own reading and research in their own time.
Data Analysis in Ecology is part of the wider Ecological Survey Techniques Programme that offers a range of standalone short courses, at its heart rests the Postgraduate Certificate in Ecological Survey Techniques aimed at those wishing to take their professional development to the next level with an Oxford qualification.
Students who successfully complete this standalone module for credit (10 CATS points at level 7) can opt to transfer their credit to the PGCert, subject to the approval of the Course Director and acceptance on to the PGCert. Students successfully transferring credit to the PGCert can expect to receive a fees discount equal to the fees paid towards the standalone module; credit can be transferred up to 2 years after having been gained and is limited to a maximum for 2 modules for transfer. In order to join the PGCert a separate application process is required.
The topics covered in the course in Data Analysis in Ecology include:
The use of statistics: What is statistics and why is it needed; Planning surveys, experiments and collecting data; Types of data
Descriptive statistics: Finding the average (mean, median, mode); Standard deviation, variance and standard error; Degrees of freedom and coefficient of variation; Descriptive statistics with QED and R
Processing and presenting data: Displaying whole data sets; displaying summarised data; Presenting data with Excel, QED and R
The normal distribution and data transformations: How to know if data are normally distributed; Using QED and R to transform data
Hypothesis testing, confidence intervals and comparisons of two sample means: Confidence intervals and testing for equal variances; Parametric vs. non-parametric tests; Paired vs. non-paired tests; Comparing means with equal or unequal variance; t-tests
Analysing frequencies: Chi-square test, goodness of fit and contingency tables; G-test; Using QED and R for each
Finding correlation: Correlation, covariance and the correlation coefficient; Pearson product moment correlation coefficient; Coefficient of determination; Spearman rank correlation coefficient; Using QED and R for each
Regression analysis: Simple linear regression; Residuals, confidence intervals, transformation of axes; Reduced major axis regression; Using QED and R for each
Introducing analysis of variance: One-way and two-way ANOVAs; Post-hoc tests; randomised block design, latin square; Using QED and R to analyse variances
When to use non-parametric statistics: Mann-Witney U-test; Wilcoxon test; Kruskall-Wallis test; Non-parametric statistics with QED and R; ANOVAs and General Linear Models; Introduction to multivariate statistics
To successfully complete the course and receive a Certificate of Attendance, active participation of at least one forum post per week, to the satisfaction of the course tutor, in the online course forums is required. The PDF sample above is an illustration only, and the wording will reflect the course and dates attended.
The University of Oxford Department for Continuing Education offers Credit Accumulation and Transfer Scheme (CATS) points for the course. Participants contributing to all the forums and successfully completing the assessment will obtain 10 CATS-equivalent points (FHEQ level 7) which may count towards a Master’s level qualification.
For information on CATS points and credit transfer, including conversion to US academic credits and European academic credits (ECTS), please visit the CATS Points FAQ page.
This course is delivered online and uses the Department’s online assignment submission system (for the course asignment). In order to meet course requirements, students will need access to the Internet and a computer meeting our recommended minimum computer specification.
In addition to the IT Requirements outlined above, students are currently required to download and install R and QED Statistics. R is increasingly used by ecologists, biologists and environmental managers to handle data (full instructions on how to download this software is available from the R website). Access to QED Statistics is provided as part of the course, however this software is not compatible with Mac or Linux operating systems. Alternative software to QED Statistics is currently being researched; where possible, students are encouraged to use R in the Data Analysis course if they are using Mac or Linux systems. Students wishing to use QED Statistics on Mac or Linux systems are advised by the programme developer Pisces Conservation Ltd to consider Windows emulation software, such as Bootcamp, to run a Windows system on their machine. For further information and a full system specification please visit the Pisces Conservation Ltd website.
Accredited study: £820.00
Non-accredited study: £510.00
Student rate (non-accredited study): £360.00
The teaching time frame covers 10 weeks, a faster paced 5 week course is scheduled for 29 October 2014. The content covered is roughly comparable to 1 week full-time study, students can expect to engage with and contribute to the course for around 5-7 hours per week depending on whether it is taken for credit or not. The course tutor will engage online for no less than 3 hours per week, this is usually distributed across each week and will focus on particular topics and activities.
There is no set time to log in to the course, which makes it ideal for students in different time zones as well as those wishing to study flexibly on a weekly basis; topics will be covered following a suggested calendar of activity, ensuring that activities, discussion and reading are completed within the 10 week duration and at an even pace with other students.
Students undertaking the course for academic credit must submit a summative written assignment of up to 2,000 words or equivalent. This is due approximately two weeks after the final day of the course. The pass mark is set at 50%, work awarded 70% or over will qualify for a distinction.
We strongly recommend that you download and save files before completing to ensure that all your changes are saved.
Apply to take the course for academic credit
If you are applying to take this course for academic credit you will need to complete and return the following documents, alongside a copy of your CV. Please ensure you read the guidance notes before completing the application form, as any errors resulting from failure to do so may delay your application.
Apply to take the course not for academic credit
If you do not wish to take this course for academic credit you will need to complete and return the following document, or use the ‘enrol online’ button below. Please ensure you read the guidance notes before completing the application form, as any errors resulting from failure to do so may delay your application.
CANDIDATES: applying for academic credit
All candidates will need to:
- Hold a minimum qualification equivalent to a first Honours Degree (BA, BSc, etc). Non-graduates may be considered if they are able to demonstrate considerable experience in a relevant field. If in doubt, please email firstname.lastname@example.org;
- Offer some first-hand knowledge and/or experience of field work or conservation issues;
- Satisfy the minimum required English language criteria set by the University, being either a native English speaker, or able to offer test results as specified. Applicants with borderline scores may be accepted on condition that they attend a language course and gain an acceptable score;
- Demonstrate an ability to be able to commit the necessary time to study;
- Have good access to a computer and a fast/reliable internet connection;
- Demonstrate an ability to work alongside fellow students and tutors as part of an online community and independently.
Where requested, this should be supplied with your application. Applicants are advised to email email@example.com should they be unsure about the suitability of the referees they intend to use.
Please note that we do not request submission of written work.
Terms and conditions
Terms and conditions for applicants and students on this course
Sources of funding
Information on financial support