Education and interlocking weights

Some polling companies weigh by educational attainment.

A former adviser to the UK government wrote on social media:

There’s literally *a BIG alignment* in UK/US over years which is why e.g pollsters now must do as Vote Leave did in 2016 & *weight by education*

What does “weight by education” mean?

In survey research, weights correct for some imbalances between samples and the population.

The typical goal of surveys is to be a representative slice of the population. Researchers adjust responses so the sample looks more like that targeted population. For example, suppose we know there are — in proportion — more women in the population than in our sample. They ‘weight’ the responses of women upwards, so they count for more. In this example, the opposite holds for men. Survey researchers will often use variables like age and gender for these weightings.

The goal of using weights is to achieve a better slice of the population. That gives more accurate survey estimates. There is a cost to this process. Weightings often increase the standard errors of those estimates.

For the 2019 General Election, four of ten polling companies used educational weights:

• Deltapoll: Age by gender, social class, household tenure work status, Government Office Region, educational attainment, 2017 General Election vote recall, 2016 EU…