# The complete solution for weighting survey data

Q contains all the tools required to weight your sample to represent the population and to use this weight appropriately in your analysis and reporting.

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#### Weights using interlocked targets (cell weighting)

Q supports cell weighting. For example, if you know that 1.2% of your population are males aged 18 to 34 living in Texas, you can weight your data so that all your analyses reflect this.

#### Weight using non-interlocked targets (rim weighting)

Construct weights even when you do not know the interlocked targets. For example, if you don’t know how many males aged 18 to 34 live in Texas, but you do know how many males are in the population, how many people aged 18 to 34, and how many Texans, you can still create a weight.

#### Weight to numeric data, such as market share (calibration)

Traditional weighting software only deals with categorical data. Q also supports the modern technique of calibration, which allows you to weight to a mix of categorical and numeric data (e.g., market share, average purchase consumption).

#### Windsorize weights (capping)

Sometimes weights generated using standard algorithms can generate weights that are too extreme (e.g., one weight of 10, another of 0.1). You can specify maximum and minimum values for weights.

#### Incorporate design weights

Sometimes studies have existing weights designed to rectify known non-representativeness (e.g., caused by stratification or differential response rates). Such design weights can be incorporated when creating new weights designed to address the overall representativeness.

#### Use multiple weights for different analyses

Specify the weight for either all analyses, or subsets of analyses (e.g., create one weight for your occasion data, and another for your household data).

#### Grossing

Easily create expansion weights to make the weighted sample add up to the population.

#### Significance tests and multivariate anlayses

The statistical tests on tables and generalized linear models (e.g., regression, driver analysis, logistic regression) address the weights via Taylor Series Linearization (i.e., they do not confuse the weighted sample size with the actual sample size).

#### Automated updating

Weights will automatically update when you revise the data, whether filtering, data cleaning, or adding in a new wave of data.

#### Complete (not just weighting)Â

Q is a general-purpose analysis app that does everything from crosstabs to text coding to advanced analysis, driver analysis, and segmentation.

Once you have weights, you can easily use them in all your subsequent analyses and reporting. There’s no need to use one package for creating weights and another package for analyzing them.

##### Increase speed

Automate manual tasks and create re-usable analysis and reports.