ABSTRACT
Chapter 13 focuses on step 7 of the research process, which is organizing and analyzing data after it has been collected. The chapter introduces some of the most common approaches to analyzing quantitative and qualitative data. Regardless of the type of data, the process of data analysis involves categorizing, organizing, interpreting, and summarizing the data in a way that answers the research question(s) posited in the research project. Quantitative data are typically organized in terms of classifying variables, and statistics are typically used to interpret findings. In some projects, quantitative data are analyzed descriptively using measures of central tendency (frequency, mean, medium, mode, range, and standard deviation). Statistical tests are also used and they vary depending on the type of data collected. The most common statistical tests used in educational research are presented and described in this chapter, including Chi-square, t-test, F-ratio, correlation, regression, factor analysis, time series analysis, and hierarchical linear modeling (HLM). In qualitative research studies, data collected in the form of interviews, document reviews, journals, and even photos are organized and interpreted in a systematic way. Some of the most common approaches to analyzing qualitative data are presented in this chapter, including content analysis, discourse analysis, narrative inquiry, case study, and grounded theory analysis. The construct of triangulation is also presented and described. Finally, different ways of organizing and presenting data are demonstrated in this chapter.
