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A short tutorial of GPower

Susanne Mayr, +3 more
- Vol. 3, Iss: 2, pp 51-59
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TLDR
GPower as mentioned in this paper is a free general power analysis program available in two essentially equivalent versions, one designed for Macintosh OS/OS X and the other designed for MS DOS/Windows platforms Psychological research examples are presented to illustrate the various features of the GPower software.
Abstract
The purpose of this paper is to promote statistical power analysis in the behavioral sciences by introducing the easy to use GPower software GPower is a free general power analysis program available in two essentially equivalent versions, one designed for Macintosh OS/OS X and the other for MS‐DOS/Windows platforms Psychological research examples are presented to illustrate the various features of the GPower software In particular, a priori, post‐hoc, and compromise power analyses for t‐tests, F‐tests, and χ2‐tests will be demonstrated For all examples, the underlying statistical concepts as well as the implementation in GPower will be described In the behavioral sciences, we routinely apply statistical tests, but control of statistical power cannot be taken for granted However, neglecting statistical power—the probability of rejecting false null hypotheses—can have severe consequences For example, without control of statistical power it is very difficult to interpret nonsignificant results Statistical tests can produce nonsignificant results because (a) the null hypothesis (H0) holds and is retained correctly or (b) the alternative hypothesis (H1) holds but the test has not been powerful enough to detect the deviations from H0 Obviously, there is no reasonable way to decide between interpretations (a) and

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A new model for assessing industrial worker behavior regarding energy saving considering the theory of planned behavior, norm activation model and human reliability

TL;DR: The results indicate that two factors of the adjusted SEM model are not statistically significant, contrary to what was expected by the TPB and the human reliability; therefore, these two factors should be the object of greater attention so as to influence the behavior of workers towards greater energy saving in industrial units.
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Augmented reality and pedestrian navigation through its implementation in m-learning and e-learning

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References
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Book

Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Journal ArticleDOI

G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

TL;DR: G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested.
Journal ArticleDOI

GPOWER: A general power analysis program

TL;DR: GPOWER performs high-precision statistical power analyses for the most common statistical tests in behavioral research, that is,t tests,F tests, andχ2 tests.
Book

Research Design and Statistical Analysis

TL;DR: Correlation Multiple Regression Regression with Categorical Variables Appendices - Notation and Summation Operations, Expected Values and Their Applications, Matrix Algebra, Statistical Tables, Control Information for Computer Programmes for Statistical Analysis.
Journal ArticleDOI

On the relationship between task performance and associated verbalizable knowledge

TL;DR: In this paper, the authors explore the relationship between performance on a cognitive task and the explicit or reportable knowledge associated with that performance (assessed here by written post-task questionnaire) and examine how this relationship is affected by task experience, verbal instruction and concurrent verbalization.
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Why use Gpower?

GPower is utilized for statistical power analysis in behavioral sciences, aiding in a priori, post-hoc, and compromise power analyses for various tests, enhancing result interpretation and research validity.