(as part of Research Fundamentals)
Learning outcomes
- Provide students with the skills and knowledge to:
• Understand various commonly used study designs and the associated strengths and weaknesses.
• Recognise some common types of sampling methodologies.
• Identify possible sources of bias and confounding.
• Distinguish between different types of data.
• Understand the difference between samples and populations and how sample statistics can be used to estimate population characteristics.
• Compute basic descriptive statistics (such as mean, median, mode, variance and IQR) and create some commonly used graphs (such as boxplots, histograms and scatterplots).
• Assess which methods for summarising a data set are most appropriate.
Course coordinator
Other statistics courses offered by RCSI
Statistics courses offered by the Data Science Centre (DSC).
| Topic | Location | Date | Time |
| Introduction and Overview of Statistics |
SSG Beaumont |
||
| Sample Size Calculations |
SSG Beaumont |
||
| Basic data recording and cleaning. |
SSG Beaumont |
||
| Descriptive statistics. |
SSG Beaumont |
||
| Graphical Presentation of Data. |
SSG Beaumont |
||
| Hypothesis Testing and Confidence Intervals. |
SSG Beaumont |
More details:
Introduction and Overview of Statistics
Topics covered will include:
- Data Cleaning and Recording – overview of how to enter and prepare data for statistical analysis.
- Descriptive Statistics – summarising and describing your data.
- Graphing Data – an outline of methods of visualising data.
- Sample Size Calculations – where to start.
- Confidence Intervals – what they are and how to interpret them.
- Hypothesis Tests – overview what a hypothesis test is and some commonly used tests.
- Measures of Association – Prevalence, Incidence, Relative Risk & Odds Ratios.
- An Introduction to Correlation and Regression- investigating relationships among variables.
The course is free and open to all but please register by clicking on the links at the top of the email.
Best wishes,