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Analyzing quantitative data can be a fairly straightforward process, because it consists of numbers and statistics. The most important factor is that the data must be compiled and reported accurately. There are some elements of data collection that are subjective, such as which specific areas are studied or which questions are asked, but the information itself is rigid in form.
The first step in analyzing quantitative data is to make a plan about the way that the information that has been collected will be organized. It also is wise to reach a consensus about the reason for gathering the data. Although the results might take the analysis in a different direction, having a plan can aid in the process of organizing data, in addition to helping to determine what sorts of information to seek.
To properly account for all responders, a distinction must be made between attempted contact and the number of responses. For example, although a certain number of surveys have been sent out, it is not likely that all of them will be returned. Responders also might fail to answer all of the questions, which can change the meaning of the results.
When analyzing quantitative data, the most illuminating results tend to come from using both numbers and percentages when reviewing information. The meaning of a percentage typically depends on how many individuals, incidents or other similar factors make up the group. It also is important to know the percentages as they relate to those numbers, so that a number has context within the larger data set.
How data is arranged is another important factor in analyzing quantitative data. Responses that have different shades of meaning can be obscured, depending on how they are arranged. For example, answers for a question with a potential for two kinds of negative responses and two kinds of positive responses can be compiled into only positive and negative responses, but that might hide how strongly people feel about a certain issue. It could be that, in those four possible answers, the trend is revealed to be further in one direction when all possible dimensions of the survey are shown.
Other factors that can be helpful in analyzing quantitative data include a good knowledge of the population that was surveyed. This includes understanding relevant information about responders, which can include factors such as education, status and age. The best group to consult will provide data that is relevant to the goal of the survey. An insufficiently diverse or otherwise inappropriate field of responders can have a negative effect on the usefulness of the results.