Graduate studies at Western
Behavioral and Brain Sciences 21 (2):226-227 (1998)
|Abstract||We demonstrate that Statistical significance (Chow 1996) includes straw man arguments against (1) effect size, (2) meta-analysis, and (3) Bayesianism. We agree with the author that in experimental designs, H0 “is the effect of chance influences on the data-collection procedure . . . it says nothing about the substantive hypothesis or its logical complement” (Chow 1996, p. 41).|
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
|Through your library||Configure|
Similar books and articles
Günther Palm (1998). Significance Testing – Does It Need This Defence? Behavioral and Brain Sciences 21 (2):214-215.
Joseph S. Rossi (1998). Meta-Analysis, Power Analysis, and the Null-Hypothesis Significance-Test Procedure. Behavioral and Brain Sciences 21 (2):216-217.
Mark Wilkinson (1997). Burning Straw Men Sheds Little Light: A Reply to Whiting and Kelly. Acta Biotheoretica 45 (1).
Brian Ribeiro (2008). How Often Do We (Philosophy Professors) Commit the Straw Man Fallacy? Teaching Philosophy 31 (1):27-38.
David Sohn (2000). Does the Finding of Statistical Significance Justify the Rejection of the Null Hypothesis? Behavioral and Brain Sciences 23 (2):293-294.
Louis G. Tassinary (1998). Significance Tests: Necessary but Not Sufficient. Behavioral and Brain Sciences 21 (2):221-222.
Stephan Lewandowsky & Murray Maybery (1998). The Critics Rebutted: A Pyrrhic Victory. Behavioral and Brain Sciences 21 (2):210-211.
Scott Aikin & John Casey (2011). Straw Men, Weak Men, and Hollow Men. Argumentation 25 (1):87-105.
Louis P. Pojman (1998). Straw Man or Straw Theory? International Journal of Applied Philosophy 12 (2):169-180.
Sorry, there are not enough data points to plot this chart.
Added to index2009-01-28
Total downloads1 ( #292,563 of 739,396 )
Recent downloads (6 months)0
How can I increase my downloads?