Hypothesis Testing
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Hypothesis Testing
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Author : Lee Baker
language : en
Publisher: Lee Baker
Release Date :
Hypothesis Testing written by Lee Baker and has been published by Lee Baker this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.
If you have a degree in statistics, you probably know how to choose the correct statistical hypothesis test and you might not learn anything from this book. Then again, you just might… Kristen Kehrer, who has a Master’s degree in statistics, said: “Lee Baker has developed a wonderful visual aid which, frankly, I wish I had when I was first learning about all the different types of test statistics”. The aid she’s talking about is a statistical test flow chart that I call The Hypothesis Wheel, and is what you’ll learn about in Hypothesis Testing. If you’re one of the 99% of researchers and analysts who use statistics but have never studied it at University, then this book is for you. Hypothesis Testing is a short guide to learning how to ask all the right questions of your data to help you in choosing the correct statistical hypothesis test, aided by The Hypothesis Wheel. It is a snappy little non-threatening book about everything you ever wanted to know (but were afraid to ask) about choosing the correct hypothesis test, answers the most frequently asked questions and inspires you to take the next steps in your journey. First, I’ll explain what statistical hypothesis testing is in simple terms. Then I’ll show you how to write a good hypothesis for your study. You’ll learn the difference between a scientific hypothesis and a statistical hypothesis, and between the Null and Alternative hypotheses. Then I’ll introduce to you the Hypothesis Wheel and show you how to use it to choose the correct hypothesis test for your study, first time, every time. By the time you’ve read Hypothesis Testing, you’ll know as much about choosing hypothesis tests as a statistician with a PhD! Yes, really. I’ve left nothing out! Hypothesis Testing makes no assumptions about your previous experience and is perfect for beginners and those just getting started with analysing data. Discover the world of hypothesis testing and choosing the correct statistical test. Get this book, TODAY!
Statistical Hypothesis Testing
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Author : Ning-Zhong Shi
language : en
Publisher: World Scientific
Release Date : 2008
Statistical Hypothesis Testing written by Ning-Zhong Shi and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Science categories.
This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during the 1978?2002 period. Emphasis is given to the process of finding appropriate statistical techniques and methods of evaluating these techniques.
Hypothesis Testing Behaviour
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Author : Fenna H. Poletiek
language : en
Publisher: Psychology Press
Release Date : 2013-05-13
Hypothesis Testing Behaviour written by Fenna H. Poletiek and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-13 with Psychology categories.
How do people search evidence for a hypothesis? A well documented answer in cognitive psychology is that they search for confirming evidence. However, the rational strategy is to try to falsify the hypothesis. This book critically evaluates this contradiction. Experimental research is discussed against the background of philosophical and formal theories of hypothesis testing with striking results: Falsificationism and verificationism - the two main rival philosophies of testing - come down to one and the same principle for concrete testing behaviour, eluding the contrast between rational falsification and confirmation bias. In this book, the author proposes a new perspective for describing hypothesis testing behaviour - the probability-value model - which unifies the contrasting views. According to this model, hypothesis testers pragmatically consider what evidence and how much evidence will convince them to reject or accept the hypothesis. They might either require highly probative evidence for its acceptance, at the risk of its rejection, or protect it against rejection and go for minor confirming observations. Interestingly, the model refines the classical opposition between rationality and pragmaticity because pragmatic considerations are a legitimate aspect of 'rational' hypothesis testing. Possible future research and applications of the ideas advanced are discussed, such as the modelling of expert hypothesis testing.
Statistical Hypothesis Testing With Microsoft Office Excel
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Author : Robert Hirsch
language : en
Publisher: Springer Nature
Release Date : 2022-07-14
Statistical Hypothesis Testing With Microsoft Office Excel written by Robert Hirsch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-14 with Mathematics categories.
This book provides a comprehensive treatment of the logic behind hypothesis testing. Readers will learn to understand statistical hypothesis testing and how to interpret P-values under a variety of conditions including a single hypothesis test, a collection of hypothesis tests, and tests performed on accumulating data. The author explains how a hypothesis test can be interpreted to draw conclusions, and descriptions of the logic behind frequentist (classical) and Bayesian approaches to interpret the results of a statistical hypothesis test are provided. Both approaches have their own strengths and challenges, and a special challenge presents itself when hypothesis tests are repeatedly performed on accumulating data. Possible pitfalls and methods to interpret hypothesis tests when accumulating data are also analyzed. This book will be of interest to researchers, graduate students, and anyone who has to interpret the results of statistical analyses.
Testing Statistical Hypotheses
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Author : Erich L. Lehmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30
Testing Statistical Hypotheses written by Erich L. Lehmann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-30 with Mathematics categories.
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Introduction To Robust Estimation And Hypothesis Testing
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Author : Rand R. Wilcox
language : en
Publisher: Academic Press
Release Date : 2016-09-02
Introduction To Robust Estimation And Hypothesis Testing written by Rand R. Wilcox and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-02 with Mathematics categories.
Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a ‘how-to’ on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions. New to this edition 35% revised content Covers many new and improved R functions New techniques that deal with a wide range of situations Extensive revisions to cover the latest developments in robust regression Covers latest improvements in ANOVA Includes newest rank-based methods Describes and illustrated easy to use software
Hypothesis Testing Made Simple
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Author : Leonard Gaston Ph.D.
language : en
Publisher: Leonard Gaston Ph.D.
Release Date : 2014-03-11
Hypothesis Testing Made Simple written by Leonard Gaston Ph.D. and has been published by Leonard Gaston Ph.D. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-11 with Mathematics categories.
This tutorial, directed primarily toward students doing research projects, is intended to help them do four things : (1) Decide if their data gathering activity can yield numerical data that will permit a meaningful hypothesis test. (2) If it will, decide if one of the tests described would be useful. (3) If so, apply that test, and (4) Adequately explain the use of the test so their readers can have confidence in their analysis. It is not intended to be a text for a complete statistics course – only a guide to few relatively simple tests . Complex hypothesis testing procedures are not covered. For example, the discussion of Analysis of Variance (ANOVA) introduces what is called one way ANOVA. Two way ANOVA, a more complex procedure involving the use of blocking variables, is not covered. It simply presents a few commonly used tests and down-to-earth explanations of how to use them. It is intended to be a low cost supplement that can help its reader understand a few commonly-used tests. It was put together on a shoestring by a non-mathematician for the benefit of other non-mathematicians -- or for mathematicians who have forgotten some or all of the statistics they have studied. There are no color illustrations or professionally-prepared charts and graphs. Economy was a guiding principle. Four brief introductory chapters discuss numbers, basic terms, measures of central tendency and dispersion, probability, and data presentation. With that background the book then introduces various tests and explains them in down to earth language.
Hypothesis Testing In Time Series Analysis
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Author : Peter Whittle
language : en
Publisher:
Release Date : 1951
Hypothesis Testing In Time Series Analysis written by Peter Whittle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1951 with Time-series analysis categories.
Nonparametric Hypothesis Testing
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Author : Stefano Bonnini
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-01
Nonparametric Hypothesis Testing written by Stefano Bonnini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Mathematics categories.
A novel presentation of rank and permutation tests, with accessible guidance to applications in R Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size. Key Features: Examines the most widely used methodologies of nonparametric testing. Includes extensive software codes in R featuring worked examples, and uses real case studies from both experimental and observational studies. Presents and discusses solutions to the most important and frequently encountered real problems in different fields. Features a supporting website (www.wiley.com/go/hypothesis_testing) containing all of the data sets examined in the book along with ready to use R software codes. Nonparametric Hypothesis Testing combines an up to date overview with useful practical guidance to applications in R, and will be a valuable resource for practitioners and researchers working in a wide range of scientific fields including engineering, biostatistics, psychology and medicine.
Wise Use Of Null Hypothesis Tests
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Author : Frank S Corotto
language : en
Publisher: Elsevier
Release Date : 2022-10-14
Wise Use Of Null Hypothesis Tests written by Frank S Corotto and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-14 with Psychology categories.
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