Voxco and Ascribe Join Forces to Enhance Your Research Capabilities
Take a peek at our powerful survey features to design surveys that scale discoveries.
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We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
VP Innovation & Strategic Partnerships, The Logit Group
Explore Regional Offices
Take a peek at our powerful survey features to design surveys that scale discoveries.
Explore Voxco
Need to map Voxco’s features & offerings? We can help!
Get exclusive insights into research trends and best practices from top experts! Access Voxco’s ‘State of Research Report 2024 edition’.
We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
VP Innovation & Strategic Partnerships, The Logit Group
Explore Regional Offices
Find the best survey software for you!
(Along with a checklist to compare platforms)
Take a peek at our powerful survey features to design surveys that scale discoveries.
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We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
VP Innovation & Strategic Partnerships, The Logit Group
Explore Regional Offices
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Sample bias in survey responses occurs when you have a question which logically categorizes the respondents, and the audience is inclined more towards a particular category/categories than the others. This results in biased survey results, meaning, you get data that favors more to a single category.
With weighting and balancing features in surveys, you can eliminate the above sample bias. This works after you have captured survey data, to evenly represent the population. You just must frame one question that will directly define the sample bias, and then weight and balance it to remove any possible sample biases.
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The obvious use of weighting and balancing is to eliminate sample bias from survey results. That does help with making accurate data-driven decisions. You do not have to worry about considering the data that could be biased or skewed, as all such data is discarded as you get survey results.
Weighting and balancing are commonly used for demographic questions related to age, gender, location, education, marital status, income, family size, etc.
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