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Related papers: Fundamentals of p-values: Introduction

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We introduce $p$-derivations and give a few basic ways in which they act like derivatives by numbers.

History and Overview · Mathematics 2023-11-23 Jack Jeffries

Selective inference is a subfield of statistics that enables valid inference after selection of a data-dependent question. In this paper, we introduce selectively dominant p-values, a class of p-values that allow practitioners to easily…

Methodology · Statistics 2024-11-22 Anav Sood

These lectures introduce key concepts in probability and statistical inference at a level suitable for graduate students in particle physics. Our goal is to paint as vivid a picture as possible of the concepts covered.

Data Analysis, Statistics and Probability · Physics 2007-05-23 Harrison B. Prosper

We point out that the traditional notion of test statistic is too narrow, and we propose a natural generalization that is arguably maximal. The study is restricted to simple statistical hypotheses.

Methodology · Statistics 2020-01-07 Yuri Gurevich , Vladimir Vovk

The logical and practical difficulties associated with research interpretation using P values and null hypothesis significance testing have been extensively documented. This paper describes an alternative, likelihood-based approach to…

Methodology · Statistics 2021-09-21 Nicholas Adams , Gerard O'Reilly

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

Probability forecasts for binary events play a central role in many applications. Their quality is commonly assessed with proper scoring rules, which assign forecasts a numerical score such that a correct forecast achieves a minimal…

Methodology · Statistics 2022-07-04 Alexander Henzi , Johanna F. Ziegel

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

In meta analysis, multiple hypothesis testing and many other methods, p-values are utilized as inputs and assumed to be uniformly distributed over the unit interval under the null hypotheses. If data used to generate p-values have discrete…

Methodology · Statistics 2026-02-24 Joshua Habiger , Pratyaydipta Rudra

In contrast to its common definition and calculation, interpretation of p-values diverges among statisticians. Since p-value is the basis of various methodologies, this divergence has led to a variety of test methodologies and evaluations…

Methodology · Statistics 2012-12-27 Tomokazu Konishi

Previously, we have introduced a very small number of examples of what we call Ouroboros functions. Using our already established theory of Ouroboros spaces and their functions, we will provide a set of families of Ouroboros functions that…

Functional Analysis · Mathematics 2021-06-10 Nathan Thomas Provost

Since its debut in the 18th century, the P-value has been an important part of hypothesis testing-based scientific discoveries. As the statistical engine accelerates, questions are beginning to be raised, asking to what extent scientific…

We propose a novel definition of Shapley values with uncertain value functions based on first principles using probability theory. Such uncertain value functions can arise in the context of explainable machine learning as a result of…

Machine Learning · Computer Science 2023-04-03 Raoul Heese , Sascha Mücke , Matthias Jakobs , Thore Gerlach , Nico Piatkowski

Analysis of credibility is a reverse-Bayes technique that has been proposed by Matthews (2001) to overcome some of the shortcomings of significance tests. A significant result is deemed credible if current knowledge about the effect size is…

Methodology · Statistics 2017-12-11 Leonhard Held

Let $(X,Y)$ be a random variable consisting of an observed feature vector $X\in \mathcal{X}$ and an unobserved class label $Y\in \{1,2,...,L\}$ with unknown joint distribution. In addition, let $\mathcal{D}$ be a training data set…

Statistics Theory · Mathematics 2008-06-26 Lutz Duembgen , Bernd-Wolfgang Igl , Axel Munk

P-value functions are modern statistical tools that unify effect estimation and hypothesis testing and can provide alternative point and interval estimates compared to standard meta-analysis methods, using any of the many $p$-value…

Methodology · Statistics 2025-02-24 Leonhard Held , Felix Hofmann , Samuel Pawel

In a recent opinion article, Muff et al. recapitulate well-known objections to the Neyman-Pearson Null-Hypothesis Significance Testing (NHST) framework and call for reforming our practices in statistical reporting. We agree with them on…

Quantitative Methods · Quantitative Biology 2022-05-30 Florian Hartig , Frédéric Barraquand

A new characterization of provably recursive functions of first-order arithmetic is described. Its main feature is using only terms consisting of 0, the successor S and variables in the quantifier rules, namely, universal elimination and…

Logic in Computer Science · Computer Science 2012-01-06 Evgeny Makarov

In this paper, we aim to introduce the concept of the Ouroboros space and the complimentary concept of the Ouroboros function by using the Ouroboros equation [1] as our starting point. We start with a few univariate definitions, and then…

Functional Analysis · Mathematics 2021-05-13 Nathan Thomas Provost

Verifying that a statistically significant result is scientifically meaningful is not only good scientific practice, it is a natural way to control the Type I error rate. Here we introduce a novel extension of the p-value - a…

Methodology · Statistics 2018-07-04 Jeffrey D. Blume , Lucy DAgostino McGowan , William D. Dupont , Robert A. Greevy