Statistics courses

Introductory Statistics for Life Scientists                                                                                       

About the course

This is an open-access course within Learn. It will introduce students to the basic principles of statistical thinking and outline some of the most common types of analysis that might be needed for Masters or PhD research projects.

You can access this course at any time of the year, there is no fixed start or end date.

Target audience

It is aimed mainly at students undertaking research projects (at either Masters or PhD level) in the College of Medicine (particularly lab-based subjects), but it may be of more general use, too - we welcome participants from any discipline, although the examples used will tend to reflect the instructors background in clinical research, public health and veterinary medicine. The principles taught, however, are universal!

Course content

Participants will use resources such as recorded PowerPoint presentations, quizzes, and directed reading to investigate a topic, and will try some practical examples in Minitab, a statistical package available on the University’s Managed Desktop and in general-access computing facilities. Support is available through discussion boards that allow queries on specific points. The course runs asynchronously – participants work on course material and exercises in their own time, and interact via the discussion boards when required.

The following topics are covered:

1. An introduction to the course and VLE
2. Basic principles of statistical inference and exploratory data analysis
3. Some basic concepts in probability
4. Confidence intervals
5. Hypothesis testing
6. Study design – randomisation and blocking
7. Study design – power calculations
8. Correlation and simple linear regression
9. One and Two-way analysis of variance models
10. Method comparison/ reproducibility studies

List of Learning Outcomes

By the end of this workshop, students should be able to:

1. Describe and apply the basic principles of statistical inference and exploratory data analysis.
2. Identify and apply basic concepts in probability
3. Define and construct confidence intervals and be able to apply hypothesis testing appropriately
4. Define randomisation, blocking and power calculations and be able to apply to study design
5. Define correlation and simple linear regression
6. Carry out one and two-way analysis of variance

Time commitment

Maximum 4 hours per week

Statistics courses on LinkedIn Learning

Statistics Foundations 1: Learn the most common statistics, including mean, median, standard deviation, probability and more, in these beginner-level statistics lessons.

Statistics Foundations 1 - find out more

Statistics Foundations 2: Get practical, example-based learning of the intermediate skills associated with statistics: samples and sampling, confidence intervals, and hypothesis testing.

Statistics Foundations 2 - find out more

Statistics Foundations 3: Complete your mastery of statistics. Get an advanced understanding of concepts such as t-distribution, degrees of freedom, chi-square testing, regression testing, and ANOVA.

Statistics Foundations 3 - find out more