Some surveys treat the respondents as representatives of the total population of which they are a sample. Normally, tables reflect the attitudes of the people interviewed, but you might want the tables to reflect the attitudes of the total population instead, so that it seems as if you had interviewed everyone rather than just a sample of the population. This, of course, assumes that the people interviewed are a truly representative sample.

If you take a sample of 380 from a population of 10,000 shoppers, and discover that 57 members of this sample buy cheddar cheese, you might want the number of shoppers who buy cheddar cheese to read 1,500 in the tables, not 57.

Moving from 57 to 1,500 is the fine art of weighting. In this case, each shopper has a weight of 10,000/380. Since 57 of them buy cheddar cheese, the number in the cell is:

Weighting is also used to correct biases that build up during a survey. For example, when conducting interviews by telephone you might find that 60% of the respondents were women. You might then want to correct this ratio of men to women to make the two groups more evenly balanced.

The basic idea behind weighting is that when someone falls into a given cell (that is, satisfies the conditions for that cell) the number in the cell is not increased by 1; rather, it is increased by 1 multiplied by the individual’s weight.