Introduction to Statistical Analysis.

This course provides a refresher on the foundations of statistical analysis.

The practical sessions use web applications that were developed specifically for this course with the R statistical programming language and the Shiny framework. Although the trainers use R as their statistical computing environment of choice, the focus of the course is on understanding basic statistical concepts rather than learning a particular statistical package.

Note that this is not a course for learning about the R statistical language. If you wish to learn more about R, please take a look at some of the other courses available at the University of Cambridge.

Trainers

• Dominique-Laurent Couturier
• Matthew Eldridge
• Mark Fernandes

Aims

During this course you will learn about:

• Different types of data, distributions and structure within data
• Summary statistics for continuous and discrete data
• Formulating a null hypothesis
• Assumptions of one-sample and two-sample t-tests
• Interpreting the result of a statistical test
• Non-parametric versions of one- and two-sample tests (Wilcoxon tests)

We will not cover ANOVA or linear regression here but these are the topics of a more advanced course.

Learning Objectives

After this course you should be able to:-

• State the assumptions required for a one-sample and two-sample t-test and be able to interpret the results of such a test
• Know when to apply a paired or independent two-sample t-test
• To perform simple statistical calculations using the online app
• Understand the limitations of the tests taught within the course
• Know when more complex statistical methods are required

Course Materials

• Lecture (pdf)
• Online quiz
• Practical

Software Requirements

You will need an internet connection in order to run the practicals and examples using the following web applications:

• Central limit theorem
• Statistical tests

Timetable

Time	Activity
9.30	Lecture
10.15	Quiz
10.30	Coffee/tea break
10.45	Lecture
11.45	Exercises (central limit theorem) & discussion
12.00	Lunch break
13.00	Lecture
13.45	Exercise (one-sample tests) and discussion
14.15	Lecture
15.00	Coffee/tea break
15.15	Exercise (two-sample tests) and discussion
15.45	Group based exercise and discussion
16.45	Wrap up & questions

Acknowledgements

The following individuals are former trainers of this course and have contributed to the materials.

• Paul Judge
• Mark Dunning
• Sarah Vowler
• Deepak Parashar
• Sarah Dawson
• Elizabeth Merrell

This course received funding from the CRUK Cambridge Centre. If you are researching cancer in Cambridge please consider becoming a member.