Why We Don't Really Know What Statistical Significance Means: Implications for Educators

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Significance tests as sorcery: Science is empirical—significance tests are not (2012, methodology): “…Finch, & Leeman, 2004; Fisher, 1955, 1956; Gigerenzer, 1987, 1993, 2004; Gigerenzer et al., 1989; Gill, 1999; Granaas, 2002; Greenwald, 1975; Hubbard & Armstrong, 2006; Hubbard & Lindsay, 2008; Hubbard & Ryan, 2000; Jones & Tukey, 2000; Kirk, 1996, 2003; Lindsay, 1995; Lykken, 1968, 1991;…”
Why P Values Are Not a Useful Measure of Evidence in Statistical Significance Testing (2008, background): “Needless to say, this has resulted in massive confusion among members of the scholarly community about exactly what ‘statistical significance’ means—is it denoted by a p value, an α level, and/or the ubiquitous p α criterion (Hubbard & Armstrong, 2006)?”
Research Commentary - Too Big to Fail: Large Samples and the p-Value Problem (2013, background): “Information Systems Research 24(4), pp. 906 –917, ©2013 INFORMS one reports point estimates and conﬁdence intervals (Hubbard and Armstrong 2006).”
Final Collapse of the Neyman-Pearson Decision Theoretic Framework and Rise of the neoFisherian (2009, background): “Likewise, though they also say that significance tests have only " marginal value, " Hubbard and Armstrong (2006) suggest that when they are employed, this should be done in a neoFisherian manner.”