Literature DB >> 27702255

Statistics for people who (think they) hate statistics Neil J Salkind Statistics for People Who (Think They) Hate Statistics Sage 420 £24.99 076192776X 076192776X [Formula: see text].

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Abstract

Strong quantitative research methods are one of the patient's strongest safeguards against dangerous bias and prejudice on the part of researchers. In addition, the evidence that algorithmic decision making outperforms 'clinical' or other human decision making by a fair margin is very strong. It is therefore sad that statistics are so feared by students, and in general are not well taught. Most books are sound on the elementary parts of statistics, but start to become difficult when more abstract concepts are covered. This book is in that tradition.

Entities:  

Year:  2005        PMID: 27702255     DOI: 10.7748/nr.12.4.89.s6

Source DB:  PubMed          Journal:  Nurse Res        ISSN: 1351-5578


  5 in total

1.  Test of age-related variation in the craniometry of the adult human foramen magnum region: implications for sex determination methods.

Authors:  René Gapert; Sue Black; Jason Last
Journal:  Forensic Sci Med Pathol       Date:  2013-04-14       Impact factor: 2.007

2.  Prospective versus predictive control in timing of hitting a falling ball.

Authors:  Hiromu Katsumata; Daniel M Russell
Journal:  Exp Brain Res       Date:  2011-11-26       Impact factor: 1.972

3.  Validation of the Head and Neck Patient Symptom Checklist as a nutrition impact symptom assessment tool for head and neck cancer patients.

Authors:  Karmen N Schmidt; Kärin Olson; Catherine Kubrak; Matthew Parliament; Sunita Ghosh
Journal:  Support Care Cancer       Date:  2012-05-16       Impact factor: 3.603

4.  Prediction of preterm deliveries from EHG signals using machine learning.

Authors:  Paul Fergus; Pauline Cheung; Abir Hussain; Dhiya Al-Jumeily; Chelsea Dobbins; Shamaila Iram
Journal:  PLoS One       Date:  2013-10-28       Impact factor: 3.240

5.  Development of Nomophobia Profiles in Education Students through the Use of Multiple Correspondence Analysis.

Authors:  Clemente Rodríguez-Sabiote; José Álvarez-Rodríguez; Daniel Álvarez-Ferrandiz; Felix Zurita-Ortega
Journal:  Int J Environ Res Public Health       Date:  2020-11-09       Impact factor: 3.390

  5 in total

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