Testing Statistical Hypotheses - SpringerLink
Develops the foundations, principles, theory, and methods of hypothesis testing; Offers new coverage of multiple hypothesis testing, high-dimensional testing, permutation, and more; Features over 100 new problems, bringing the total to …
Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions
Learn how to test means, medians, variances, proportions, distributions, counts, correlations for continuous and categorical data, and find outliers. One-Way ANOVA, Two-Way ANOVA, and interaction effects. Check assumptions to obtain reliable results.
Testing Statistical Hypotheses (Springer Texts in Statistics)
2023年6月25日 · Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite-sample theory, while the second volume discusses large-sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance.
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Testing Statistical Hypotheses (Springer Texts in Statistics)
2005年1月1日 · 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 …
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[2410.23614] Hypothesis testing with e-values - arXiv.org
2024年10月31日 · This book is written to offer a humble, but unified, treatment of e-values in hypothesis testing. The book is organized into three parts: Fundamental Concepts, Core Ideas, and Advanced Topics. The first part includes three chapters that introduce the basic concepts.
Identify the four steps of hypothesis testing. Define null hypothesis, alternative hypothesis, level of significance, test statistic, p value, and statistical significance. Define Type I error and Type II error, and identify the type of error that researchers control. Calculate the one-independent sample z test and interpret the results.
Statistical Hypothesis Testing in Context - Cambridge …
Bringing practical statistical science to AI and predictive model fairness testing. AI and Ethics, Fay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation.
New eBook Release! Hypothesis Testing: An Intuitive Guide
By reading this book, you will build a solid foundation for understanding hypothesis tests and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and how to interpret the results correctly.
Hypothesis Testing: An Intuitive Guide for Making Data Driven …
2020年9月17日 · Learn how to test means, medians, variances, proportions, distributions, counts, correlations for continuous and categorical data, and find outliers. One-Way ANOVA, Two-Way ANOVA, and interaction effects. Check assumptions to obtain reliable results. Manage the error rates for false positives and false negatives.
Introduction to Robust Estimation and Hypothesis Testing
Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful ‘how-to’ on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity ...
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