ABSTRACT
This chapter describes the basic principles for analyzing quantitative data and some of the most common analytical methods in technical communication research. Whenever inferences are made based on measurements taken from a sample, two standards of rigor must be addressed: validity and reliability. Internal validity addresses the question “Did you measure the concept that you wanted to study?” External validity addresses the question “Did what you measured in the test environment reflect what would be found in the real world?” Descriptive statistics describe a specific set of data—usually the sample population. Inferential statistics make inferences about a larger population based upon sample data. Hypothesis testing allows you to see whether an intervention makes a difference. It tests the assumption that results from the control group and the test group will be alike. Random selection means that the selection and assignment of each test participant is independent and equal. What type of data you choose and what you want to learn from them determine the type of statistical calculations that you should perform. Statistical calculations described in this chapter include standard deviation, t-test, analysis of variance (ANOVA), correlation analysis, regression analysis, and the chi-square test.
