Analysing & Forecasting COVID19 Trends - Virtual Classroom

Date: Thursday 09 July 2020 9.30AM - Friday 10 July 2020 1.00PM
Location: Online
CPD: 6.0 hours
RSS Training
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Our COVID19 world is one where data driven decision making is now more important than ever. A key part of this is interpreting what the current trends in number of cases, deaths and test results all mean and whether there are differences between certain groups.  The follow up question is what will happen in the future which involves modelling and extrapolation of existing trends in order to make forecasts of the future.

 

Course Outline

Our COVID19 world is one where data driven decision making is now more important than ever. A key part of this is interpreting what the current trends in number of cases, deaths and test results all mean and whether there are differences between certain groups.  The follow up question is what will happen in the future which involves modelling and extrapolation of existing trends in order to make forecasts of the future.

All the methods needed to do this are regularly used in business planning in all industries.  The course will concentrate on analysing & forecasting COVID19 data but the methods can be applied elsewhere. Due to the way COVID19 data is collected in the UK, this course will focus on data from England for ease of comparability but the same methods can be used for other nations of the UK and indeed for any location in the world.

By the end of the course you will have a firm grasp of how to summarise, measure & interpret trends as well as how to extrapolate trends into a forecast. You will also have a good understanding of how to perform relevant calculations in Excel.
 

Learning Outcomes

  • Learn about the 6 key COVID19 datasets for England and what their strengths and weaknesses are.
  • Understand the distinction between sober & drunk time series (seriously!)
  • Learn how to use confidence intervals to confirm that a trend is a genuine trend and that turning points are real.
  • Learn how to use moving averages correctly to identify potential turning points.
  • Discover the simplest method of identifying seasonality in your time series.
  • Uncover the basic principles of SPC and how you can use SPC to confirm deviations from an expected trend.
  • Learn 4 different ways of extrapolating an existing trend to produce a forecast.
  • Understand the key principles of forecasting, learn to spot common mistakes in forecasting and become better at prediction.
 

Topics Covered

Time series analysis, forecasting, trend identification, seasonality, moving averages, trend extrapolation, statistical process control.
 

Target Audience

Anyone involved in business planning, performance analysis and other similar roles that require analyses of historical trends and extrapolation of those trends to create forecasts.
 

Knowledge Assumed

It is assumed that participants will be comfortable creating charts in Microsoft Excel and are using formulae and are familiar with basic statistical concepts such as means, standard deviations and correlations.  It is helpful but not essential if participants have some knowledge of logarithms, linear regression, confidence intervals and hypothesis testing.

 

Nigel Marriott

Nigel Marriott is a chartered statistician who provides statistical consulting, training and data management services to clients in many industries. Nigel has accrued a wealth of experience working with research, intelligence, planning and forecasting teams within a broad range of areas such as: purchasing, finance, trading desks, sales, marketing, product design, IT, engineering, manufacturing, quality and scientific fields. This is highly unusual in any profession, but particularly for a statistician, who tend to specialise in particular fields and this has given him fluency in many varieties of technical and non-technical English. His ability to communicate with any audience from boardroom to shop floor, a high level of commercial awareness and the experience to see how one part fits into the bigger picture are some of the many reasons why his services are highly sought after both nationally and internationally.

 

Fees

   

Registration before
 09 June 2020

 

Registration on/after
 09 June 2020

                                  

Non Member 

RSS Fellow 

RSS CStat/Gradstat also MIS & FIS 

 

£392.00+vat 

£332.00+vat 

£314.00+vat

£435.00+vat 

£370.00+vat 

£349.00+vat

 
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