Statistical thinking

Course level: foundation

Next live course dates: TBC Click here to request training details.

Course description

Many people assume that statistics require complex analysis methods but often, the simplest approaches can be the most effective. This course focuses on the concept of statistically thinking, describing data and complex systems in relatively simple terms whilst acknowledging underlying uncertainty.

Statistical thinking is a necessary skill, not just in work but in our personal lives too. We are constantly bombarded by data via the news and social media. Often the claims made here are exaggerated or skewed to fit a certain narrative. Thinking statistically allows us to sift through all these conflicting claims and make our own minds up based on evidence.

The process of statistical thinking involves critically appraising available data, identifying patterns using visualisations and summaries, and communicating results in a clear, concise manner. Statistical thinking could be thought of as data-driven critical thinking. This course does not introduce any complex analysis methods, nor does it require the use of any statistical software. No prior statistical training is required.

Outline

Topics covered in this course include:

• The importance of a clear, well-defined research question and how to formulate this
• Common biases and how to recognise them
• Data visualisation as a tool to explore data, investigate trends, and convey important messages
• Summarising data and quantifying differences or trends
• Interpreting inferential statistics

Target audience

This course was originally designed for the UK Ministry of Justice’s data analysts.

This course was designed for those with little or no background in mathematics or statistics, who would like to critically appraise data or interpret results based on statistical principles. This course does not introduce complex analysis methods, nor does it require the use of statistical software.

Learning outcomes

By the end of this course, participants will be able to:

• Formulate a clear, well-defined research question
• Choose appropriate data visualisations to explore data or communicate results, and know when to question others’ choices of visualisation
• Understand how to choose the most appropriate summary statistics to quantify elements of data, interpret these values, and know when certain summaries would be invalid
• Interpret confidence intervals and p-values