ONS Economic Statistics Courses

Courses Developed by the Economic Statistics Working Group

EML Learning is running a series of Economic Statistics training courses on behalf of the ONS Economic Statistics Working group. The group comprises of nominees from the Royal Economic Society (RES), the Royal Statistical Society (RSS), the Office for National Statistics (ONS), the Economic Statistics Centre of Excellence (ESCOE) and the Society of Professional Economists (SPE). The group has a remit to improve capability in economic statistics and are introducing a programme of activities aimed at improving quality and understanding.

Inequality and poverty analysis

FaceToFace
Face-to-face

Tutor-led in a classroom

This course provides an introduction to the ways in which analysts measure inequality and poverty, addressing conceptual issues and practical matters including data. There are also hands-on sessions in the computer lab.

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National Accounts

FaceToFace
Face-to-face

Tutor-led in a classroom

The course is voluntarily directed to non-experts. While it covers the theoretical definition of the main national accounts aggregates, it does it in a lively manner based on the concrete experience of the teacher.

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Prices

FaceToFace
Face-to-face

Tutor-led in a classroom

One of the most important economic statistics published by the ONS has been the inflation rate: first measured by RPI, more recently by CPI and currently also by CPIH. This two-day course will start by briefly exploring the economic and statistical theory behind the construction of these price indices.

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Understanding Data and Basic Statistics

FaceToFace
Face-to-face

Tutor-led in a classroom

This practical, two-day workshop will present an overview of the manipulations of data that are often required prior to statistical analysis. Topics will include dealing with outliers, combining data from different sources, calculating annual average growth rates, weighting and smoothing data and constructing indexes. It was also cover basic statistical methods used in describing data such as measures of central tendency and dispersion, correlation and the use of dummy variables in regression analysis.

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