Weighting is a technique that adjusts the results of a survey to bring them into line with some known characteristics of the population. For example, if a sample contains 40% males and the population contains 49% males, weighting can be used to correct the data to correct for this discrepancy.
A weight variable, which is often simply referred to as the weights, is a variable used when weighting data during analysis. In most situations, when people refer to weights they are referring to sampling weights. However, there are other types of weights. See Overview of Weighting for more information.
Most outputs in Displayr that have been computed using a Variable Set as an input can be weighted by selecting the output and choosing a weight.
Technical details
R Calculations and weights
R Calculations on the page have access to weighting information applied, see Weights in R for more info.
Ignoring weights
For a small number of analysis methods, such as hierarchical cluster analysis and distance calculations, weights are and should be ignored, where the calculations are based on differences between individual cases.
Placement
The weight variable should be in the same data set used for the analysis (you may need to paste in the values as a new variable in the raw data editor or merge the weighted values into your data set to do this). However, you can also use a variable in a different data set as long as there is a relationship linking the data sets together, but this weight value will be applied to all matching cases and not adjusted by the number of matching cases.
Method
For Displayr: How to Configure a Weight from Variable(s) Click Here for an Interactive Tutorial on Weighting