"Q. Why does sample size matter?
A. Because the risk of random sampling error is related to sample size: the smaller the sample, the greater the risk of such error. On a sample of 550, we can be sure that, 19 times out of 20, the true figure – that is, the figure that would have been obtained had the whole population been polled using the same methods – is within 4% of the published figure. Random error on a sample of 1,000 is up to 3%, on 1,500 up to 2.5% and on 2,000 up to 2%. Larger samples also allow the views of subgroups, such as women voters or Conservative supporters, to be measured more accurately."