Key Concepts: Data Analysis Techniques

Powell

• The basic purpose of statistical analysis is to summarize observations/data in such a manner that they provide answers to a hypothesis or research question.
• Descriptive statistics deal with the tabulation of data: their presentation is in tabular, graphical, or pictorial form.  This kind of statistical analysis can characterize what is typical in a group, indicate how widely cases in the group vary, show relationships between variables and groups, and summarize data.
• Inferential statistics are used for making inductive generalizations about populations based on sample data and for testing hypotheses.  This kind of statistical analysis can estimate population parameters and test the significance of relationships between and among variables.

Wildemuth

• Content analysis is the systematic, objective, quantitative analysis of message characteristics.  This form of data analysis is only interested in content characteristics related to the hypothesis or research question.  A set of codes is to capture those characteristics is developed and finalized before analysis begins.  Content analysis is deductive and can deal with large, randomly selected samples.
• Chi-square statistic measures the difference between what was observed and what would be expected in the general population.  The chi-square statistic can be used to test the null hypothesis that there is no relationship between the two variables.