Inferential statistics

Course level: Foundation

Self-paced course available FREE here

Course description

The aim of statistical analysis is often to make inferences about a target population of interest based on a random sample from it. Inferences such as these require inferential statistics.

This micro-course will introduce two of the most common inferential statistics: p-values and confidence intervals. Although these statistics are widely used across many disciplines, their interpretation can be tricky, which can lead to them being misrepresented. Here, we demystify the theory behind the p-value and confidence intervals, show how they are calculated, and give a worked example with detailed interpretations.

Developed for and hosted by the wonderful Equations of disease.

Outline

Topics covered in this course include:

• Measures of precision
• The central limit theorem
• Confidence intervals
• p-values

Target audience

Anyone that would like to carry out statistical analysis as part of their and would like inferential statistics explained in straightforward language.

Participants are expected to have a basic understanding of summary statistics, such as the mean, but can take this course with no prior statistical training. The course does not require any software.

Learning outcomes

Upon completion of the ‘Inferential statistics’ micro-course, participants will understand the meaning of p-values and confidence intervals, and be able to accurately interpret these values.