- 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
- 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
- Finding correlation: Correlation, covariance and the correlation coefficient; Pearson product moment correlation coefficient; coefficient of determination; Spearman rank correlation coefficient
- Regression analysis: Simple linear regression; residuals, confidence intervals, transformation of axes; reduced major axis regression
- Introducing analysis of variance: One-way and two-way ANOVAs; post-hoc tests; randomised block design, latin square
- When to use non-parametric statistics: Mann-Witney U-test; Wilcoxon test; Kruskall-Wallis test; non-parametric statistics; ANOVAs and General Linear Models; introduction to multivariate statistics
Your course tutor will guide you through a series of key topics via reading materials, online activities, and discussion forums. Discussion forums are 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.
Level and demands
The course is designed for Master’s-level students, and you are likely to be studying alongside students on our Postgraduate Certificate in Ecological Survey Techniques.
You can expect
- To engage with and contribute to the course around ten to 15 hours per week (depending on whether it is taken for credit or not). Note that we also offer a less intense ten-week version of this course
- Your course tutor will engage online for no less than six hours per week (usually distributed across each week and will focus on particular topics and activities).
- Topics to be covered following a suggested calendar of activity (so that activities, discussion and reading are completed within the course week duration, and at an even pace).
- The 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.