Employers Skills Survey

This is a template. Please copy the contents into a new page to create your actual spec sheet.

• Submitted by: David Owen, d.w.owen@warwick.ac.uk
• Submitted on: April 11, 2013
• Revision; 1 (Revision goes up whenever spec sheet is unclear and needs to be clarified)

This data load contains 3 files, which are as follows:

This data comes from the ASHE dataset, date of dataset, conditions, warnings, etc.

Describe briefly steps taken, if any, to convert data from source data into the files you are submitting.

These files contain the following columns:

• SOC - the SOC code.
• gender - gender coding. Refer to coeff.csv and previous ASHE datasets.
• region - region coding. Refer to coeff.csv and previous ASHE datasets.
• …
• WeightP - a weight against the sum of observations of this data point.
• WeightInc - number of observations, to be summed and weighted against WeightP to yield the true earnings figure.

… information about coefficients file here …

The output of queries on this dataset is the estimated weekly pay of persons matching the filtering dimensions, given in pounds sterling. Note that the dataset does not contain averages between multiple filtering expressions; these must be calculated in the querying software.

To receive the estimated weekly pay for a set of filtering conditions, query by these conditions and then apply the weightings as follows (this is a made-up example!):

• For all matching observations, take the sum of the estimated pay and multiply by the sum of WeightInc divided by WeightP.
• In other words, weekly_pay_weighted = (sum(pay * WeightInc) / sum(WeightP))

An example: suppose you want to average the weekly pay across both males and females in London. To do so,

• calculate the weekly pay for males and the weekly pay for females in London.
• add both and divide by the sum of observations for both males and females.

• …
• …