Frank S Corotto

Wise Use of Null Hypothesis Tests (eBook, ePUB)

A Practitioner's Handbook

• Format: ePub

Produktbeschreibung

Few students sitting in their introductory statistics class learn that they are being taught the product of a misguided effort to combine two methods into one. Few students learn that some think the method they are being taught should be banned. Wise Use of Null Hypothesis Tests: A Practitioner's Handbook follows one of the two methods that were combined: the approach championed by Ronald Fisher. Fisher's method is simple, intuitive, and immune to criticism.



Wise Use of Null Hypothesis Tests is also a user-friendly handbook meant for practitioners. Rather than overwhelming the reader with endless mathematical operations that are rarely performed by hand, the author of Wise Use of Null Hypothesis Tests emphasizes concepts and reasoning. In Wise Use of Null Hypothesis Tests, the author explains what is accomplished by testing null hypotheses-and what is not. The author explains the misconceptions that concern null hypothesis testing. He explains why confidence intervals show the results of null hypothesis tests, performed backwards. Most importantly, the author explains the Big Secret. Many-some say all-null hypotheses must be false. But authorities tell us we should test false null hypotheses anyway to determine the direction of a difference that we know must be there (a topic unrelated to so-called one-tailed tests). In Wise Use of Null Hypothesis Tests, the author explains how to control how often we get the direction wrong (it is not half of alpha) and commit a Type III (or Type S) error.

• Offers a user-friendly book, meant for the practitioner, not a comprehensive statistics book
• Based on the primary literature, not other books
• Emphasizes the importance of testing null hypotheses to decide upon direction, a topic unrelated to so-called one-tailed tests
• Covers all the concepts behind null hypothesis testing as it is conventionally understood, while emphasizing a superior method
• Covers everything the author spent 32 years explaining to others: the debate over correcting for multiple comparisons, the need for factorial analysis, the advantages and dangers of repeated measures, and more
• Explains that, if we test for direction, we are practicing an unappreciated and unnamed method of inference

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 210
• Erscheinungstermin: 14. Oktober 2022
• Englisch
• ISBN-13: 9780323952859
• Artikelnr.: 66109906

Autorenporträt

Frank S. Corotto earned his bachelor of science in biology at Lafayette College in Pennsylvania, his master of arts in biology at Boston University, and his doctorate in biological sciences at the University of Missouri-Columbia. He worked as a post doc at the University of Utah's Department of Physiology then went on to teach biology at North Georgia College, later renamed North Georgia College & State University, for 17 years and at the University of North Georgia for eight years. While initially a neurobiologist, he researched in other fields including animal behavior, plant reproduction, and ciliate feeding selectivity. Because of his interest in experimental design, he discovered a primary literature on null hypothesis testing that ran counter to what is in traditional statistics books. The result is Wise Use of Null Hypothesis Tests: A Practitioner's Handbook.

Inhaltsangabe

Chapter 1. The conventional method is a flawed fusion
1.1 Three statisticians, two methods, and the mess that should be banned
1.2 Wise use and testing nulls that must be false
1.3 Null hypothesis testing in perspective

Chapter 2. The point is to generalize beyond our results
2.1 Samples and populations
2.2 Real and hypothetical populations
2.3 Randomization
2.4 Know your population, and do not generalize beyond it

Chapter 3. Null hypothesis testing explained
3.1 The effect of sampling error
3.2 The logic of testing a null hypothesis
3.3 We should know from the start that many null hypotheses cannot be correct
3.4 The traditional explanation of how to use p
3.5 What use of a accomplishes
3.6 The flawed hybrid in action
3.7 Criticisms of the flawed hybrid
3.8 We should test nulls in a way that answers the criticisms
3.9 How to use p and a
3.10 Mouse preference, done right this time
3.11 More p-values in action
3.12 What were the nulls and predictions?
3.13 What if p50.05000?
3.14 A radical but wise way to use p
3.15 0.05 or .05? p or P?

Chapter 4. How often do we get it wrong?
4.1 Distributions around means4.2 Distributions of test statistics
4.3 Null hypothesis testing explained with distributions
4.4 Type I errors explained
4.5 Probabilities before and after collecting data
4.6 The null's precision explained
4.7 The awkward definition of p explained
4.8 Errors in direction
4.9 Power and errors in direction
4.10 Manipulating power to lower p-values
4.11 Increasing power with one-tailed tests
4.12 Power and why we should we set a to 0.10 or higher
4.13 Power, estimated effect size, and type M errors
4.14 How can we know a population's distribution?

Chapter 5. Important things to know about null hypothesis testing
5.1 Examples of null hypotheses in proper statistics books and what they really mean
5.2 Categories of null hypotheses?
5.3 What if is important to accept the null?
5.4 Never do this
5.5 Null hypothesis testing as never explained before
5.6 Effect size: what is it and when is it important?
5.7 We should provide all results, even those not statistically "significant

Chapter 6. Common misconceptions
6.1 Null hypothesis testing is misunderstood by many
6.2 Statistical "significance means a difference is large enough to be important-wrong!
6.3 p is the probability of a type I error-wrong!
6.4 If results are statistically "significant, we should accept the alternative hypothesis that something other than the null is correct-wrong!
6.5 If results are not statistically "significant, we should accept the null hypothesis-wrong!
6.6 Based on p we should either reject or fail to reject the null hypothesis-often wrong!
6.7 Null hypothesis testing is so flawed that we should use confidence intervals instead-wrong!
6.8 Power can be used to justify accepting the null hypothesis-wrong!
6.9 The null hypothesis is a statement of no difference-not always
6.10 The null hypothesis is that there will be no significant difference between the expected and observed values-very, very wrong!
6.11 A null hypothesis should not be a negative statement-wrong!

Chapter 7. The debate over null hypothesis testing and wise use as the solution
7.1 The debate over null hypothesis testing
7.2 Communicate to educate
7.3 Plan ahead
7.4 Test nulls when appropriate, not promiscuously
7.5 Strike the right balance between what is conventional and what is best
7.6 Think outside of the null hypothesis test
7.7 Encourage our audience to draw their own conclusions
7.8 Allow ourselves to draw our own conclusions
7.9 Strike the right balance when providing our results
7.10 Know the misconceptions and do not fall for them
7.11 Do not say that two groups "differ or "do not differ
7.12 Provide all results somehow
7.13 Other reform