Statistical Analysis with Survey Software

Posted on : January 2, 2015 - by :

After you have collected your data, you need to analyze it.  Most survey software only offers primitive analytical tools.  Their publishers expect you to export the data to another package for detailed analysis.  There are a few exceptions, such as The Survey System.

There are three main types of analysis that are commonly used with questionnaire data.  The first is to determine how likely the answers you received represent the answers of the whole population you are studying.  In the case of determining how closely you can take percentages of your respondents picking an answer to represent that larger population, you can use a simple sample size calculator.  Commonly, this wouldn’t be part of a table you would include a report, but would instead be an overall comment on the survey.

The second kind of statistics is descriptive.  The most common of these is probably a mean, which tells you the average answer you received.  Related statistics include standard deviations, standard errors and medians.  Some programs let you include these on your tables.

The third kind of statistics is probabilistic.  These tell you how likely differences you see between different groups of people in your sample represent differences in the corresponding population.  One common example is the difference between proportions test (sometimes called Z test), which is used to estimate how likely a difference seen between the percentages of one group of people picking an answer choice and another group picking the same choice in your sample represent real differences in the population.  Another example is a t-test.  This test does the same thing for means that the difference between proportions test does for percentages.

Another kind of statistics quantifies relationships between answers to two or more questions.  Correlation and multiple regression are common techniques here.  Both are used mainly to compare the answers to two or more questions in which the numbers used to represent the answers are meaningful.  For example, if you ask people how much money they spend each month on food, the answer is a number that would itself be meaningful.  If you ask people their gender and code men as 1 and women as 2, those numbers are not meaningful, they just signify a difference.

Descriptive and probabilistic statistics are usually shown on tables showing how different groups of people answered your questions.  Statistics such as correlation and regression are most often presented as separate reports.

Using survey software that includes statistical analysis among its features will save you time compared to any program that requires you to export your data to do sophisticated analysis.

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