Content
In this course, you will be introduced to the fundamental principles of statistics and to ways of conducting your own analysis, including significance tests and linear regression techniques. The excellent free software R studio will be introduced and used for all practical aspects of the course which is a user-friendly interface for R. We will cover:
• An overview of quantitative research study designs
• Types of data
• Graphical displays
• Summaries of data
• Confidence intervals
• Hypothesis testing (parametric and non-parametric tests)
• p-values
• Linear Regression analysis
No prior knowledge of R or statistical analysis is required.
Concessions
A 50% discount is available for UCL staff, students, alumni. If you're eligible for a discount, email ich.statscou@ucl.ac.uk before booking to be sent the discount code.
The course is available for free to those associated with the Institute of Child Health or Great Ormond Street Hospital, and UCL doctoral students. Please also email ich.statscou@ucl.ac.uk to gain a booking code.
Learning outcomes
At the end of the course, learners should understand the main principles of collecting good data and producing statistics using the R software package.
In particular, learners will be able to:
• Set out a plan of analysis for a research question accounting for all types of data involved and aspects of their question.
• Choose the best way of graphically displaying their data and results.
• Choose the significance tests suitable to answer their question.
• Make appropriate use of statistical inference methods.
• Understand when regression methods are useful.
• Choose the most suitable regression model for their analysis.
• Evaluate the goodness of fit of the fitted model.
• Perform appropriate model diagnostics and predictions.
• Perform all the above analyses in the R studio software package.
Find out about other statistics courses
CASC's stats courses are suitable for anyone requiring an understanding of research methodology and statistical analyses. The courses allow non-statisticians to interpret published research and/or undertake their own research studies.
Find out more about CASC's full range of statistics courses.
