Data Analysis for Ecologists and Field Biologists

This tutor-led 10-week ecological statistics course provides a thorough introduction to the key statistical principals 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.

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, past students on the Ecological Survey Techniques programme have joined us from the UK, the USA, Australia, Africa and Europe.

Data Analysis aims to create a quality workshop experience by encouraging student and tutor interaction and discussion in an online setting.

This course can be taken with or without Masters-level accreditation; accreditation enables students to demonstrate their academic achievement and can count towards further postgraduate study. Students taking the course with accreditation submit an assessment of up to 2000 words or equivalent, while students taking the course without accreditation will receive a Certificate of Attendance upon successful completion of the course.

Data Analysis will require students to purchase the core text Fowler et al (1998) Practical Statistics for Field Biology.

Each topic is covered via guided reading, online activities, and discussion forums. All the reading material is embedded into the course, but students additionally have access to the University's electronic resources and online journals, which they are expected to use for some of the activities. Participants are expected to study on, and contribute to, the course for around 10-15 hours per week. If the course is being taken for credit, participants will need to complete an assessment. There is a suggested calendar of activity which students can use to assist them in completing the course within the allocated five week duration.

Topics covered by the course:

1. The use of statistics: What is statistics and why is it needed; Planning surveys, experiments and collecting data; Types of data
2. 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
3. Processing and presenting data: Displaying whole data sets; displaying summarised data; Presenting data with Excel, QED and R
4. The normal distribution and data transformations: How to know if data are normally distributed; Using QED and R to transform data
5. 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
6. Analysing frequencies: Chi-square test, goodness of fit and contingency tables; G-test; Using QED and R for each
7. 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
8. Regression analysis: Simple linear regression; Residuals, confidence intervals, transformation of axes; Reduced major axis regression; Using QED and R for each
9. 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
10. 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

“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”

“I can say with a full confidence that thanks to this course I finally understand stats and know how to do it myself!”

Past students on Data Analysis in Ecology

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 with accreditation 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.

Certification

Non-accredited Study

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.

Accredited Study

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.

Fees

Accredited study: £820.00
Non-accredited study: £510.00
Student rate (non-accredited study): £360.00