It is crucial that you consider reporting a main element of your web survey design at the outset of your research project. What you can say about your results hinges heavily on the types of analyses your questions and the capabilities of your response scales.
Today, we will outline the difference between the two major branches of statistical analysis available for most survey data: descriptive and inferential.
What is descriptive statistics?
Descriptive statistics are the basic measures used to describe survey data. They consist of summary descriptions of single variables (also called “univariate” analysis) and the associated survey sample. Examples of descriptive statistics for survey data include frequency and percentage response distributions, measures of central tendency (which include the mean, median and mode), and dispersion measures such as the range and standard deviation, which describe how close the values or responses are to central tendencies.
What is inferential statistics?
Inferential statistics offer more powerful analyses to be performed on your online web survey data. As the names suggests, this branch of statistics is concerned with making larger inferences about social phenomena. This can include associations between variables, how well your sample represents a larger population, and cause-and-effect relationships. Some examples of inferential statistics commonly used in survey data analysis are t-tests that compare group averages, analyses of variance, correlation and regression, and advanced techniques such as factor analysis, cluster analysis and multidimensional modeling procedures.
By designing online questionnaires and survey web forms with a good idea of what you want to do with your data after it's collected, you can create cohesive, powerful reports and presentations.
