`There are few people who can write about research methods in a lively and engaging way, but Miles and Banyard are amongst them. As well as being an exceptionally clear introduction to research methods, it is full of amusing asides and anecdotes that make you want to read more. A hugely enjoyable book' - Dr Andy Field, University of Sussex ......
Maruyama uses a single data set to demonstra te a variety of techniques which range from path analysis, b y way of panel analysis and confirmatory analysis, to latent variable structural equation modelling. '
Graphical displays that researchers can employ as an integral part of the data analysis process are frequently more revealing than traditional, numerical summary statistics. Providing strategies for examining data more effectively, this volume focuses on: univariate methods such as histograms, smoothed histograms, univariate scatterplots, quantile ......
'This book should prove to be an important addition to the relatively few publications that exist on statistical thinking. It very nicely encourages the reader to take an active learning approach through simultaneously promoting pedagogy with knowledge and skills enhancement in statistics. Understanding what the subject is for and what it can do are crucial in statistical education - by getting the reader to think statistically Mr Graham has provided us with a very readable book that helps to dispel the poor reputation that statistics has acquired over many years' - Professor Neville Davies, Director, Royal Statistical Society Centre for Statistical Education, Nottingham Trent University Statistics is a key area of the school mathematics curriculum where maths and the real world meet. Although potentially a subject where teaching can be motivating and relevant to everyday concerns, it is often seen as boring and involving largely mechanical calculations. This book will enable teachers and others interested in statistical thinking to become excited and inspired by the big ideas of statistics and, in turn, teach them enthusiastically learners. Designed to heighten awareness of statistical ideas, the book explores key themes within statistics using ideas developed by the influential team at The Open University's Centre for Mathematics Education. Themes include: * Measurement * Variation * Randomness * Uncertainty Arranged in an accessible task-based format, this is an essential text for all secondary maths teachers and students of maths education. It is a comprehensive book that will illuminate and inspire interest in the subject, based on innovative use of ICT, engaging narrative, firm research and good practice. Developing Thinking in Statistics is a set book on the Open University Course ME626 Developing Statistical Thinking, part of the Graduate Diploma in Mathematics Education.
'This book should prove to be an important addition to the relatively few publications that exist on statistical thinking. It very nicely encourages the reader to take an active learning approach through simultaneously promoting pedagogy with knowledge and skills enhancement in statistics. Understanding what the subject is for and what it can do are crucial in statistical education - by getting the reader to think statistically Mr Graham has provided us with a very readable book that helps to dispel the poor reputation that statistics has acquired over many years' - Professor Neville Davies, Director, Royal Statistical Society Centre for Statistical Education, Nottingham Trent University Statistics is a key area of the school mathematics curriculum where maths and the real world meet. Although potentially a subject where teaching can be motivating and relevant to everyday concerns, it is often seen as boring and involving largely mechanical calculations. This book will enable teachers and others interested in statistical thinking to become excited and inspired by the big ideas of statistics and, in turn, teach them enthusiastically learners. Designed to heighten awareness of statistical ideas, the book explores key themes within statistics using ideas developed by the influential team at The Open University's Centre for Mathematics Education. Themes include: * Measurement * Variation * Randomness * Uncertainty Arranged in an accessible task-based format, this is an essential text for all secondary maths teachers and students of maths education. It is a comprehensive book that will illuminate and inspire interest in the subject, based on innovative use of ICT, engaging narrative, firm research and good practice. Developing Thinking in Statistics is a set book on the Open University Course ME626 Developing Statistical Thinking, part of the Graduate Diploma in Mathematics Education.
Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper level techniques to cater for the advanced student.
This book provides encouragement and strategies for researchers who routinely address research questions using data from small samples. Chapters cover such topics as: using multiple imputation software with small sets; computing and combining effect sizes; bootstrap hypothesis testing; when to use latent variable modeling; time-series data from ......
This bestselling textbook is designed to help students understand parametric and nonparametric statistical methods so that they can tackle research problems successfully. By working through this book carefully and systematically, those who may not have a strong background in mathematics will gain a thorough grasp of the most widely used statistical methods in the social sciences.
Significance testing is a core topic in statistics because it is a useful technique for testing a hypothesis. Mohr introduces the reader to the topic by first reviewing what is meant by sampling distributions and probability distributions, and then examining in-depth normal and t-tests of significance. In addition to these topics, Mohr explores the uses and misuses of significance testing.
