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.
Shows them the meanings of the statistics they are computing. • This book is easy to digest because it is divided into short sections with review questions at the end of each section. • Running sidebars draw students’ attention to ...
MAKING SENSE OF STATISTICS: A Conceptual Overview
Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective.
Kruskal-Wallis. and. Friedman. So far, we have focused on drilling down into data following one-way ANOVA. Of course, if one of the rank-based alternatives were used, it is still possible to carry out post hoc analysis, although these ...
... with tick marks of 0, 10, 20, 30, 40 and 50. A logarithmic scale, or log scale, when applied to an axis of a graph, is a scale in which numbers increase through addition. For example, a logarithmic scale might start at 1, ...
Pearson's product‐moment correlation coefficient is valid only for certain probability distributions, including the normal and the Student's t‐distribution. You compute the Spearman's rank correlation coefficient by converting sample ...
A further messy situation is when we have low communalities for some observed variables, suggesting that the current factor analysis solution does not account for an acceptable amount of the variance of those variables.
... for everyone who has ever been afraid of statistics, Pearson Education Inc., Upper Saddle River, 2005 MONTGOMERY, D. C., ... I. H, and E. FRANK, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, ...
Making Sense of Statistics
This book aims to help readers navigate this morass: to understand the debates, to be able to read and assess other people's statistical reports, and make appropriate choices when designing and analysing their own experiments, empirical ...