Increasingly, public sector organisations are turning to statistics to help drive performance, improve decision making and deliver better services. Within 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 analyse data reports and develop effective forecasting strategies.
This course gives professionals with a limited understanding of statistics the confidence to make more effective decisions based on statistical reports produced by analysts and researchers.
Take an active part throughout the day, using a mixture of computer models on spreadsheets, practical examples, interactive learning tasks and theory.
Please can delegates bring their own laptops. You will only need excel to complete statistical tasks.
What previous delegates have said:
“An excellent introduction, pitched to the right level.”- Business Intelligence and Data Analytics Manage, Leeds University
“Excellent course. I feel like I have learnt a lot in relaxed conditions.”- Data Management Officer, Mersey Travel
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
- Trends and prediction
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
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 units
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 Chair 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
- Measures of prediction uncertainty
- Group discussion: why do forecasts go wrong? How can we reduce the risk of this happening?
- Overcome common cognitive biases
- Exercise on putting it all together: which team deserves a bonus?
16:00 - 16:15
Feedback, Evaluation & Close
etc. Venues – Marble Arch, London
86 Edgware Road
020 7793 4200
A: Unfortunately, we do not accept provisional bookings. Registrations are subject to our terms and conditions. View terms and conditions here
A: Yes. Simply email [email protected] after you have booked the course, with your Purchase Order Number. Please quote your order number and the course you are booked onto.
A: Yes, a two-course hot buffet is served at lunch. Tea and coffee are served throughout the day.
A: Special dietary requirements can be catered for, please ensure you include this in the further information box when registering your place. If you have forgotten to add this, you can also send your requirements to [email protected] or call 0800 542 9440. Please let us know as soon as possible so we can ensure your needs are met.
A: You will receive the joining instructions and reminders, 2 weeks, 1 week and 3 days before the course date. Please check your spam box to see whether the joining instructions were sent there, if not please call 0800 542 9440 so we can have these sent to you immediately.
A: Substitutions may be made at any time but must be made no later than 48 hours prior to the event. Please call 0800 542 9440 or email [email protected] with the replacement's details.
A: Cancellations must be received in writing 30 working days before the date of the event and will be subject to a £195+VAT administration fee. Cancellations received after this time will be subject to the full delegate fee.
A: Speakers presentations are sent a week after the event date. Please contact a member of the UMG team on 0800 542 9440 or [email protected] if it has been more than a week.
A: Yes, all our venues have the latest technology, offer full audio visual support and WI-FI.
A: Why not contact a member of the UMG team on 0800 542 9440 or email [email protected]