Statistical Weighting Methods

When you’re looking for a statistical weighting procedure or application, it is very important to remember that the key to a balanced and representative sample is controlling for known biases in comparison with the target population.

From all the different statistical procedures that exist today, such as rim weighting, propensity weighting, cell weighting it is safe to say that iterative proportional fitting – aka ranking – is the method most used by researchers.

Our tool at uses this method too, since it’s a very flexible and easy-to-use method that allows for multiple variables. You can include these in your weighting scheme to control the match of your sample with the target population.

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Statistical Weighting

When you want to be certain that you’re sample is representative for the population you’ve studied you can use a technique or procedure called statistical weighting. If you’re looking for a representative sample, it has to be of the same composition as the population that you’re studying.

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How to Assign Weights to Variables

Has anyone ever asked you about sampling weights, what they are or how they are calculated? I’m here to tell you what sampling weights is and how it’s done. With sampling for surveys, you can always end up with a sample that is not perfectly representative of your known population. For instance, the age or gender might be off or skewed a bit, and you may have to calculate the weights that fix this bias in your sample.

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