In today’s data-driven world, statistical analysis plays a pivotal role in organisational decision-making. The ability to effectively analyse and interpret statistical data is crucial for professionals in the public sector who aim to improve performance, make more informed decisions and plan for the future.
Designed specifically for non-statisticians in the public sector, Understanding Statistical Analysis will demystify statistical terminology and provide you with the practical tools you need to analyse and apply statistics to your organisation’s work.
Learn how to mitigate risks, build useful forecasting strategies and interpret data-heavy reporting. Statistics can be an incredibly powerful tool and this course will help you unlock your potential to analyse and apply them effectively.
Alex is an experienced statistician, speaker and tutor who uses a range of data sources and presentational methods to help hospitals and clinicians improve their performance.
After his first job as a statistician with a large pharmaceutical company, Alex moved to Imperial College London and gained a PhD in Epidemiology. He was seconded to the Shipman Public Inquiry to investigate how statistics could be used to detect GPs like Shipman with high death rates. Since 2002, his research has focused on measuring the quality and safety of healthcare using large databases and on helping clinicians ...
Trainer’s Welcome and Clarification of Learning Objectives
First Steps: Some Basic Statistical Terms
- What is statistical thinking and why does it matter?
- Types and examples of quantitative data: continuous, categorical, count
- Some common distributions in the real world, e.g. normal, bimodal, uniform, skewed
- When averages are misleading
- Key terms such as mean, mode, median, percentile, standard deviation, range, ratio, probability and risk, odds, accuracy vs precision
Understanding Variation 1: Describing Variation and Randomness
- Quantifying variation
- What is randomness? Why and when is it a problem
- Exercise: quick demo of randomness in action
- The role of chance and how to assess it (hypothesis testing)
- Exercise on assessing how much variation exists between teams
Understanding Variation 2: Sampling Strategies and Bias
- Options for surveying customers and staff: sampling strategies
- Measurement error and precarious data
- Exercise: how satisfied are my customers?
Associations and Trends
- Correlation vs. causation
- The linear trend: concept of least squares and choosing line of best fit
- Types of trends: linear, exponential rise or fall, step change, seasonal, other non-linear
- Exercise: what’s the trend here?
Forecasting and Getting It Wrong
The Trainer will facilitate a group discussion around the ways in which forecasts can go wrong and the ways to reduce the risk of this happening
- Extrapolating from a linear trend
- How to choose between linear and non-linear trends in Excel
- Common cognitive biases that affect data interpretation and decision making