The Search for Significance: Seeing Your True Worth Through God's Eyes

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The Search for Significance: Seeing Your True Worth Through God's Eyes

The Search for Significance: Seeing Your True Worth Through God's Eyes

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Hald, Anders (1998), "Chapter 4. Chance or Design: Tests of Significance", A History of Mathematical Statistics from 1750 to 1930, Wiley, p.65 Ioannidis, John P. A. (2005). "Why most published research findings are false". PLOS Medicine. 2 (8): e124. doi: 10.1371/journal.pmed.0020124. PMC 1182327. PMID 16060722. Sproull, Natalie L. (2002). "Hypothesis testing". Handbook of Research Methods: A Guide for Practitioners and Students in the Social Science (2nded.). Lanham, MD: Scarecrow Press, Inc. pp. 49–64. ISBN 978-0-810-84486-5. García-Pérez, Miguel A. (2016-10-05). "Thou Shalt Not Bear False Witness Against Null Hypothesis Significance Testing". Educational and Psychological Measurement. 77 (4): 631–662. doi: 10.1177/0013164416668232. ISSN 0013-1644. PMC 5991793. PMID 30034024.

The use of a one-tailed test is dependent on whether the research question or alternative hypothesis specifies a direction such as whether a group of objects is heavier or the performance of students on an assessment is better. [3] A two-tailed test may still be used but it will be less powerful than a one-tailed test, because the rejection region for a one-tailed test is concentrated on one end of the null distribution and is twice the size (5% vs. 2.5%) of each rejection region for a two-tailed test. As a result, the null hypothesis can be rejected with a less extreme result if a one-tailed test was used. [40] The one-tailed test is only more powerful than a two-tailed test if the specified direction of the alternative hypothesis is correct. If it is wrong, however, then the one-tailed test has no power. Health, David (1995). An Introduction To Experimental Design And Statistics For Biology (1sted.). Boston, MA: CRC press. pp.123–154. ISBN 978-1-857-28132-3. Clarke, GM; Anderson, CA; Pettersson, FH; Cardon, LR; Morris, AP; Zondervan, KT (February 6, 2011). "Basic statistical analysis in genetic case-control studies". Nature Protocols. 6 (2): 121–33. doi: 10.1038/nprot.2010.182. PMC 3154648. PMID 21293453. Another common analysis in which P values can easily be misinterpreted is the selection of a prediction model for multiple regression or classification. To show how this can occur, we performed 1,000 simulations of our 10 physiological variables that were, as before, random and independent of each other and of SBP. We then applied forward selection to identify variables that statistically predicted SBP. In this selection process, we start with no variables in the model and iteratively add the variables that provide the most statistically significant improvement, repeating this until no further variables add to the explanatory power of the model.

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Woolston, Chris (2015-03-05). "Psychology journal bans P values". Nature. 519 (7541): 9. Bibcode: 2015Natur.519....9W. doi: 10.1038/519009f. The widespread abuse of statistical significance represents an important topic of research in metascience. [59] Redefining significance [ edit ]

Pedhazur, Elazar J.; Schmelkin, Liora P. (1991). Measurement, Design, and Analysis: An Integrated Approach (Studented.). New York, NY: Psychology Press. pp.180–210. ISBN 978-0-805-81063-9. Brian, Éric; Jaisson, Marie (2007). "Physico-Theology and Mathematics (1710–1794)". The Descent of Human Sex Ratio at Birth. Springer Science & Business Media. pp.1–25. ISBN 978-1-4020-6036-6.

a b Myers, Jerome L.; Well, Arnold D.; Lorch, Robert F. Jr. (2010). "Developing fundamentals of hypothesis testing using the binomial distribution". Research design and statistical analysis (3rded.). New York, NY: Routledge. pp.65–90. ISBN 978-0-805-86431-1. To begin, research predictions are rephrased into two main hypotheses: the null and alternative hypothesis.

Not just "theoretical," this book has also been extremely practical for me. God has used this book and the things he showed me about my life to keep me from making an enormous mistake by leaving my church. I had no idea just how much my living, reacting, and responding to many things was out of my past until God showed me through this material. In doing this, in working through the material in this book, I have peace in a situation I never could have imagined. In fact, I am resolved, committed, more than I have ever been. There are various critiques of the concept of statistical significance and how it is used in research. One by one, The Search For Significanceconfronts these lies, dismantles them, and points you to a higher truth that is the source of life’s meaning. It points you to Almighty God—the source of life itself. Siegfried, Tom (2015-03-17). "P value ban: small step for a journal, giant leap for science". Science News . Retrieved 2016-12-01. Really enjoyed this perspective from McGee. The book is fairly simple in that it covers 4 main areas of false belief about ourselves that we so often operate out of. He then outlines the corresponding core fears associated with these; fear of failure, rejection, punishment, and hopelessness.Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp.62–67. "The use of p values for nearly a century [since 1925] to determine statistical significance of experimental results has contributed to an illusion of certainty and [to] reproducibility crises in many scientific fields. There is growing determination to reform statistical analysis... Some [researchers] suggest changing statistical methods, whereas others would do away with a threshold for defining "significant" results." (p. 63.) That said, this book was beyond disappointing. The author's understanding of deep, chronic psychotic depression was non-existent as he never even mentioned that. He mentioned some information on very remedial depression, though, and through this information, totally and completely misrepresented what true depression really is. The sort of "snap out of it" mentality is just the very thing that had lead to some of my specific ideation, that said, this book is one of the WORST books to put into a person's hands who is suffering from a Psychotic episode due to Depression. For example, when α {\displaystyle \alpha } is set to 5%, the conditional probability of a type I error, given that the null hypothesis is true, is 5%, [37] and a statistically significant result is one where the observed p-value is less than (or equal to) 5%. [38] When drawing data from a sample, this means that the rejection region comprises 5% of the sampling distribution. [39] These 5% can be allocated to one side of the sampling distribution, as in a one-tailed test, or partitioned to both sides of the distribution, as in a two-tailed test, with each tail (or rejection region) containing 2.5% of the distribution. We conclude, based on our review of the articles in this special issue and the broader literature, that it is time to stop using the term "statistically significant" entirely. Nor should variants such as "significantly different," " p ≤ 0.05 {\displaystyle p\leq 0.05} ," and "nonsignificant" survive, whether expressed in words, by asterisks in a table, or in some other way. See also [ edit ]



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