In this course you will learn how to make statistically valid generalisations: that is, how to generalise your findings from a sample to a wider population. This process is called statistical inference.

Your sample of data is just one instance of a countless number of possible samples that could have been drawn from the same population. It follows that the value of any statistic that is calculated from your sample is only an estimate of its true value in the population. You must therefore attach a measure of precision to your estimate.

To that end, these concepts are covered:

  • Sampling variability of an estimate
  • Standard error as a measure of precision
  • The Normal distribution
  • Confidence intervals: how to calculate and interpret them.

Screen duration

At the top of each screen you will see an indication of the approximate time it will take to complete the screen, including video lengths and time for reflection where appropriate.

You are currently working through the programme designed for Engineering and Technology researchers. Statistics is needed within any discipline that gathers data and needs to quantify and interpret it. We have tried to illustrate the theory with relevant examples for this discipline but of course it cannot be personalised for every specific research need. You may find it helpful to also investigate the other disciplinary areas within the Epigeum programme:

  • Biomedical Sciences
  • Business
  • Natural Sciences
  • Social Sciences.

Course features

To consolidate learning and give a feel for how the statistical concepts and skills under discussion can be applied in areas of research, this programme features:

  • Videos of researchers discussing their experiences with statistics
  • Worked examples of statistical analysis using different sets of data
  • The opportunity to practise statistical concepts on a dataset, assessed by a multiple choice quiz
  • Support for several different statistical software packages.

More information

You will find pop-up pods of this nature spread throughout the course. They are organised into the following categories:

Download (containing further information to download and save)

Glossary (containing a downloadable list of key terms)

Key terms (definitions of particular terms)

More information (more information or useful links)

Statistics packages (instructions and advice for using different statistics packages. We support GenStat® 16, Instat+® 3.37, Minitab® 16, R 3.0, SAS® 9.3, IBM® SPSS® Statistics 21 and Stata® 13.)

Statistics in the real world (examples of Statistics beyond your research)

Your context (indicating areas where you may need to find out the policy at your particular institution or in your subject area)

Pods

On the right-hand side of many of the course screens, you will find 'pods' containing extra information, activities, or helpful download documents. For example, there is one on the right-hand side called 'More information'. Click on these pods to reveal more.

In-text pods

There are also pods within the main text that allow you to download or access information that is essential to the course.

Glossary

Click the following link to download a glossary of the key terms which will be used in this course:

You will find a complete glossary of all the key terms used in this programme in the 'Introduction' screen of the course 'Conclusion: Putting your skills into practice'.