The Eight Steps of Data Analysis: A Graphical Framework to Promote Sound Statistical Analysis

Data analysis is a risky endeavor, particularly among people who are unaware of its dangers. According to some researchers, “statistical conclusions validity” threatens all research subjected to the dark arts of statistical magic. Although traditional statistics classes may advise against certain pr...

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Bibliographic Details
Published in:Perspectives on psychological science Vol. 15; no. 4; pp. 1054 - 1075
Main Author: Fife, Dustin
Format: Journal Article
Language:English
Published: Los Angeles, CA SAGE Publications 01.07.2020
SAGE PUBLICATIONS, INC
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ISSN:1745-6916, 1745-6924, 1745-6924
Online Access:Get full text
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Summary:Data analysis is a risky endeavor, particularly among people who are unaware of its dangers. According to some researchers, “statistical conclusions validity” threatens all research subjected to the dark arts of statistical magic. Although traditional statistics classes may advise against certain practices (e.g., multiple comparisons, small sample sizes, violating normality), they may fail to cover others (e.g., outlier detection and violating linearity). More common, perhaps, is that researchers may fail to remember them. In this article, rather than rehashing old warnings and diatribes against this practice or that, I instead advocate a general statistical-analysis strategy. This graphic-based eight-step strategy promises to resolve the majority of statistical traps researchers may fall into—without having to remember large lists of problematic statistical practices. These steps will assist in preventing both false positives and false negatives and yield critical insights about the data that would have otherwise been missed. I conclude with an applied example that shows how the eight steps reveal interesting insights that would not be detected with standard statistical practices.
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ISSN:1745-6916
1745-6924
1745-6924
DOI:10.1177/1745691620917333