- Sheffield - 5th March 2020
- 09:30am - 5pm
- Pam Liversidge Building, Design Studio 1, D06
This course provides a refresher on the foundations of statistical analysis. The course is aimed at scientists at all levels – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since. The focus of the course is on understanding the principles behind statistical testing, how to choose and execute the most appropriate test for your data, and how to interpret the result.
Note that you will need to be familiar with R to access this course. We have a course scheduled for March 3rd that will cover sufficient background https://sbc.shef.ac.uk/training/r-introduction-2020-03-03/
Provisional Timetable and Materials
- 09:30 - 10:00 - Introduction to Statistical Analysis, Lecture
- 10:00 - 10:30 - Contingency tables, and testing for categorical variables, Lecture
- 10:30 - 11:30 - Contingency tables, and testing for categorical variables, Practical - including tea and coffee
- 11:30 - 12:00 - Normality, outliers and descriptive statistics, Lecture
- 12:00 - 13:00 - LUNCH
- 13:00 - 14:00 - Normality, outliers and descriptive statistics, Practical
- 14:00 - 17:00 - Significance tests for continuous variables, Lecture and Practical - including tea and coffee
See this presentation for an overview of the R code used
- Please download and unzip this file
- We would be grateful if you could fill in this feedback form which will help us improve the course for the future.
Who should attend this course?
The course is aimed primarily at scientists at all levels – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since.
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 R
- Understand the limitations of the tests taught within the course
- Know when more complex statistical methods are required
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
- Statistical tests of categorical variables (Chi-squared and Fisher’s exact tests)
- Non-parametric versions of one- and two-sample tests (Wilcoxon tests)
You will need to bring an internet-enabled laptop to the course and install the latest versions of both R and RStudio before coming to the course
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select “Run as administrator” instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.
You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run
sudo apt-get install r-base and for Fedora run
sudo yum install R). Also, please install free the RStudio IDE.
- Introductory-level R; for example attending our Data Manipulation and Visualisation course
- Mark Dunning, Bioinformatics Core Director
- Aya Elwazir, PhD Student
- Tim Freeman, PhD Student