How to make sense of statistics / Stephen Gorard.

Format:

Book

Author/Creator:

Gorard, Stephen, author.

Contributor:

Rosengarten Family Fund.

Language:

English

Subjects (All):

Social sciences--Statistical methods.

Social sciences.

Statistics.

Physical Description:

xxii, 289 pages : illustrations ; 25 cm

Place of Publication:

London ; Thousand Oaks, CA : SAGE, [2021]

Summary:

"In a new textbook designed for students new to statistics and social data, Stephen Gorard focuses on non-inferential statistics as a basis to ensure students have basic statistical literacy. Understanding why we have to learn statistics and seeing the links between the numbers and real life is a crucial starting point. Using engaging, friendly, approachable language this book will demystify numbers from the outset, explaining exactly how they can be used as tools to understand the relationships between variables. This text assumes no previous mathematical or statistical knowledge, taking the reader through each basic technique with step-by-step advice, worked examples, and exercises. Using non-inferential techniques, students learn the foundations that underpin all statistical analysis and will learn from the ground up how to produce theoretically and empirically informed statistical results."--Publisher's description.

Designed for students new to statistics and social data, author Stephen Gorard focuses on non-inferential statistics as a basis to provide readers with fundamental statistical literacy. Assuming no previous statistical knowledge, Gorard demystifies the subject in an engaging and approachable style.

Contents:

Part I: Introduction

Why we use numbers in research

What is a number? Issues of measurement

Part II: Basic analyses

Working with one variable

Working with tables of categorical variables

Examining differences between real numbers

Significance tests: how to conduct them and what they do not mean

Significance tests: why we should not report them

Part III: Advanced issues for analysis

The role of judgement in analysis

Research designs

Sampling and populations

What is randomness?

Handling missing data: the importance of what we don't know

Handling missing data: more complex issues

Part IV: Modelling with data

Errors in measurements

Correlating two real numbers

Predicting measurements using simple linear regression

Predicting measurements using multiple linear regression

Assumptions and limitations in regression

Predicting outcomes using logistic regression

Data reduction techniques

Part V: Conclusion

Presenting data for your audience.

Notes:

Includes bibliographical references (pages 278-286) and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Rosengarten Family Fund.

ISBN:

9781526413826

1526413825

9781526413819

1526413817

OCLC:

1250366263

Publisher Number:

99995776791