Statistics without Mathematics

SAGE PUBLICATIONS LTDISBN: 9781473902459

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By David J Bartholomew
Imprint:
SAGE PUBLICATIONS LTD
Release Date:
Format:
PAPERBACK
Dimensions:
234 x 156 mm
Weight:
300 g
Pages:
192

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Description

This is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.

David J Bartholomew was a professor of statistics at the London School of Economics. He is now retired.

Introduction: Before We Begin Chapter 1: Picturing Variability Chapter 2: Interpreting Variability Chapter 3: Three Standard Distributions Chapter 4: Summarising Variation Chapter 5: The Analysis of Variation Chapter 6: Covariation Chapter 7: Sampling Chapter 8: Introduction to the Ideas of Inference Chapter 9: Sampling Distributions and More on Inference Chapter 10: Inference about Averages Chapter 11: Binary Data Chapter 12: Goodness of fit Chapter 13: Unobserved Variables Chapter 14: Retrospect Apendix

Bartholomew brings a wealth of experience to this book, explaining all of the most fundamental concepts in statistics with insight but without technicalities. This is an excellent read for the learner or the teacher, to establish or reinforce a proper understanding of what statistics is really all about. -- Neil Sheldon

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