G*Power 3

G*Power 3 is a major extension of, and improvement over, G*Power 2. It covers statistical power analyses for many different statistical tests of the F test, t test, χ2-test and z test families and some exact tests. G*Power 3 offers five different types of statistical power analysis: A priori (sample size N is computed as a function of power level 1-β, significance level α, and the to-be-detected population effect size), Compromise (both α and 1-β are computed as functions of effect size, N, and an error probability ratio q = β/α), Criterion (α and the associated decision criterion are computed as a function of 1-β, the effect size, and N), Post-hoc (1-β is computed as a function of α, the population effect size, and N), Sensitivity (population effect size is computed as a function of α, 1-β, and N), G*Power 3 provides improved effect size calculators and graphics options. It supports both a distribution-based and a design-based input mode. G*Power 3 is available for Mac OS X 10.4 and Windows XP/Vista. G*Power 3 is free.

References in zbMATH (referenced in 13 articles )

Showing results 1 to 13 of 13.
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  1. Ly, Cheng; Marsat, Gary: Variable synaptic strengths controls the firing rate distribution in feedforward neural networks (2018)
  2. Zhao, Kun; Kashima, Yoshihisa; Smillie, Luke D.: From windfall sharing to property ownership: prosocial personality traits in giving and taking dictator games (2018)
  3. Füllbrunn, Sascha C.; Luhan, Wolfgang J.: Decision making for others: the case of loss aversion (2017)
  4. Barbieri, Christina; Booth, Julie L.: Support for struggling students in algebra: contributions of incorrect worked examples (2016) MathEduc
  5. Chen, Cheng-Huan; Chiu, Chiung-Hui: Employing intergroup competition in multitouch design-based learning to foster student engagement, learning achievement, and creativity (2016) MathEduc
  6. Goodman, Sara G.; Seymour, Travis L.; Anderson, Barrett R.: Achieving the performance benefits of hands-on experience when using digital devices: a representational approach (2016) MathEduc
  7. Herbst, Patricio; Chazan, Daniel; Kosko, Karl W.; Dimmel, Justin; Erickson, Ander: Using multimedia questionnaires to study influences on the decisions mathematics teachers make in instructional situations (2016) MathEduc
  8. Mansouri, S. Afshin; Aktas, Emel; Besikci, Umut: Green scheduling of a two-machine flowshop: trade-off between makespan and energy consumption (2016)
  9. Glöckner, Andreas; Hilbig, Benjamin E.; Jekel, Marc: What is adaptive about adaptive decision making? A parallel constraint satisfaction account (2014) MathEduc
  10. Janczyk, Markus; Pfister, Roland: Understanding inference statistics. From A for significance test to Z for confidence interval (2013)
  11. Li, Yuelin; Baron, Jonathan: Behavioral research data analysis with R (2012)
  12. Wollschläger, Daniel: Foundations of data analysis with R. An application oriented introduction. (2010)
  13. Güleşir, Gürcan; van den Berg, Klaas; Bergmans, Lodewijk; Akşit, Mehmet: Experimental evaluation of a tool for the verification and transformation of source code in event-driven systems (2009) ioport

Further publications can be found at: http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/literature