1.

Record Nr.

UNINA990006972750403321

Autore

Boccaccio, Giovanni <1313-1375>

Titolo

Il Decameron / Giovanni Boccaccio ; a cura di Aldo Francesco Massera

Pubbl/distr/stampa

Bari : Laterza, 1955

Descrizione fisica

2 v. ; 22 cm

Collana

Scrittori d'Italia

Locazione

BAT

Collocazione

BIB. BAT.3391(1)

BIB. BAT.3391(2)

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9911019984103321

Autore

Cahusac Peter <1957->

Titolo

Evidence-based statistics : an introduction to the evidential approach from likelihood principle to statistical practice / / Peter M.B. Cahusac

Pubbl/distr/stampa

Hoboken, NJ : , : Wiley, , [2021]

ISBN

9781119549819

1119549817

9781119549826

1119549825

9781119549833

1119549833

Descrizione fisica

1 online resource

Disciplina

519.5

Soggetti

Mathematical statistics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

The Evidence is the Evidence -- The Evidential Approach -- Two Samples -- ANOVA -- Correlation and Regression -- Categorical Data -- Nonparametric Analyses -- Other Useful Techniques -- Orthogonal Polynomials -- Occam's Bonus -- Problems with p Values.

Sommario/riassunto

Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches. The evidential approach is conceptually easier to grasp, and the calculations more straightforward to perform. This book explains how to express data in terms of the strength of statistical evidence for competing hypotheses.   The evidential approach is currently underused, despite its mathematical precision and statistical validity. Evidence-Based Statistics is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book.   While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician's "bag of tricks." In this book:    * It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion  * Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that's 'too good to be true', multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps)  * Equations are given for all analyses, and R statistical code provided for many of the analyses  * Sample size calculations for evidential probabilities of misleading and weak evidence are explained  * Useful techniques, like Matthews's critical prior interval, Goodman's Bayes factor, and Armitage's stopping rule are described  Recommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields, Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis.