Increasingly, public sector organisations are turning to statistics to help drive performance, improve decision making and deliver better services. With this growing dependency on statistics, there is an increasing need for more professionals to be able to think in a more statistical way.
By attending this Understanding Statistical Analysis course, delivered by statistician Alex Bottle, gain the skills to mitigate risk when making decisions, confidently interpret data-based reports and develop simple but effective forecasting strategies.
This course gives professionals with no or only a limited understanding of statistics the confidence to make more effective decisions based on statistical reports produced by analysts and researchers.
NB: Delegates who attend the day will be asked to bring their own laptops.
About the Chair: Alex Bottle
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 and managers to improve standards through better use and presentation of data.
A Fellow of the Higher Education Academy, he teaches statistics and critical appraisal of evidence to medical and other science students. He runs training sessions on the use and interpretation of healthcare performance data for customer support managers at his unit’s longstanding commercial partners and their NHS and international customers. Find out more.
09:15 - 09:45
09:45 - 10:00
Trainer's Welcome & Clarification of Learning Objectives
The Trainer will introduce the main concepts to be covered during the course, including:
- Types of data and common distributions
- Measuring and understanding variation
- Correlation, trends and linear forecasting
10:00 - 10:45
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
- Why the jury acquitted OJ Simpson of murder and why this matters to your analysis
10:45 - 11:00
11:00 - 12:00
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
12:00 - 13:00
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?
14:00 - 14:45
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?
14:45 - 15:00
15:00 - 16:00
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
16:00 - 16:15
Feedback, Evaluation & Close
etc. Venues – Prospero House, London
241 Borough High St
020 7105 6030
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