A quantitative researcher often seek to know what percentage of people do one thing or another, whereas a qualitative researcher pays more attention to individual cases and the human understandings in those cases.
Quantitative tools gather numerical and statistical data using experiments, measurements, fixed-response questionnaires, test scoring, and so on. The approach is underpinned by 'scientific' world views of cause and effect, belief in the objectivity of the researcher and the search for truth.
Surveys are the primary method of quantitative research – research with some claim to statistical accuracy.
A well-designed survey is critical to quantitative research. There are three ingredients to a well-designed questionnaire:
-A clear understanding of the research objectives and the product, concept, or issue.
-An ability to write clear, intelligent questions using language common to the surveys respondents.
-Attention to the surveys flow & logic so respondents are only asked appropriate questions and not asked those that do not pertain to their situation.
There are two types of survey errors: a) non-sampling error and b) sampling error. Both can be controlled. Non-sampling error results from poor questionnaire construction, low response rates, non coverage (missing a key part of the market), and processing weaknesses.
The other type of error is sampling error. Sampling is the process of deciding what portion(s) of your market you will survey, including who and how many. The goal of sampling techniques is to reduce (or eliminate) sampling error. In the ideal world, you wouldn’t need sampling, and there would be no sampling error. You would (and could) survey all customers (called a census), and they would all respond.
Proper sampling means reaching the right audience in large enough numbers to be confident that you know what your market feels and thinks.
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