The purpose of this chapter is to summarize the collected data and the statistical treatment, and/or mechanics, of analysis. The first paragraph should briefly restate the problem, taken from Chapter 1. Explain the object of each experiment, question, or objective, point out salient results, and present those results by table, figure, or other form of summarized data. Select tables and figures carefully. Some studies are easier to defend if all the raw data is in this chapter; some are better if the bulk of the raw data is in an appendix.
In a quantitative study, the results usually begin with a description of the sample (e.g., sample size, description of participants who were excluded and why, handling of missing data). Next, descriptive statistics (e.g., frequencies/percentages for categorical variables, means, standard deviations, and ranges for continuously measured variables) are presented.
Normality of continuously measured variables is usually presented. Address each hypothesis in turn, presenting a description of the analysis that was computed to address each hypothesis and the results of that analysis. State whether the null hypothesis was rejected.
Do not repeat in tedious prose what it is obvious for a knowledgeable peer to see at a glance. The dissertation advisor usually has an opinion about the level of detail needed in this chapter. Table titles and figure captions should be understandable without reading the chapter text. Note all relevant results, even those that were contrary to the alternative hypotheses, or those that tend to distract from clear determinations.
Make statements of the results without any implication, speculation, assessment, evaluation, or interpretation. Sometimes the results and discussion are combined into one chapter, but in general, keep the results, and the conclusions and discussion separate.
In a qualitative study, the results often include many quotes from participants who were interviewed.<< Writing Chapter 3: MethodologyWriting Chapter 5: Discussion and Recommendations >>
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