Chapter 19 Study Guide: Processes of Quantitative Data Analysis and Interpretation

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Study Guide: Chapter 19, Processes of Quantitative Data Analysis and Interpretation Pre-Analysis Treatment of Data Transforming and Coding Quantitative Data The units used for quantifying variable data should be consistent throughout the study. Data collected through survey instruments should be treated in a manner that accurately reflects the intended goals of the study. For example, answers to survey questions, such as ethnic identity, may retrieve more than one answer. How the researchers handle this situation may have an impact on the relevance of the findings. Data Entry, Verification, and Cleaning The quality of the study will depend on how carefully the researchers entered the data into software programs and verified its correctness. Verification can occur visually or by entering the data twice. Cleaning the data involves the identification of possible outliers by looking at the frequency distribution of the data in a graphical format, such as a scatterplot, followed by testing suspected outliers statistically. Visual inspection of the data should also reveal the presence of wild codes, which are values that make no sense. The data in its final form must therefore be verified for correctness and cleaned of outliers and wild codes. Handling Missing Values Missing data is usually handled through deletion or imputation. If the frequency of missing values is low, all of the data from subjects with missing data might be deleted, otherwise an entire variable may be
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