Weighting factors are used in sampling to make samples match the population. For example, let’s say we did a survey and 41% or respondents were female and 59% were male. We know from census data that females should make up 51% of the population and males 49%.  In order to model a more representative sample, we might add a little more “weight” to data from females.

Rather than dispose of additional surveys we can include the views of more respondents while balancing the overall responses to be more representative of the Canadian population at large.

When reputable pollsters apply weights to data they always disclose this. In Canada it is common industry practice to be transparent about methodology and to delineate between weighted and unweighted results.

An example of how a gender weight is calculated

To calculate how much weight you might need for a gender weight one would divide the known population percentage by the percent in the sample.

• Known population females (51) / Sample Females (41) = 51/41 = 1.24.
• Known population males (49) / Sample males (59) = 49/59 = .83.