
Exploratory and Descriptive Statistics
SAGE Publications Ltd (Publisher)
1st Edition
Published on 21. March 2022
Book
Paperback/Softback
256 pages
978-1-5264-2471-6 (ISBN)
Description
Nervous about statistics?
This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
More details
Series
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Dimensions
Height: 244 mm
Width: 170 mm
Thickness: 15 mm
Weight
448 gr
ISBN-13
978-1-5264-2471-6 (9781526424716)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Professor Julie Scott Jones is a professor of sociology and the former Head of the Department of Sociology at Manchester Metropolitan University. Julie has had a career long interest in social science research methods, editing seven books on the subject, including volumes on applied ethics. She was the founder and original Director of the Manchester Metropolitan University Q-Step Centre, which received GBP1.15 million in funding from the Nuffield Foundation-ESRC-HEFCE. Q-Step was an ambitious programme to change the training of quantitative methods and data literacy in social science students. She has co-authored several journal articles on the pedagogy of quantitative methods teaching, based on her current research in this field. In 2022 her co-authored textbook Exploratory and Descriptive Statistics (2022) was published by SAGE. Julie currently teaches quantitative data analysis and data management to final year undergraduate students.
Dr John E. Goldring is the Co-Director of the Q-Step Centre at Manchester Metropolitan University, one of 15 centres across the UK to receive funding to promote the development of quantitative methods teaching across the HE sector. Joining Manchester Metropolitan University in 2004, his initial research and teaching focus was on men, masculinity and health. He started teaching statistical analysis in 2012 where he developed a narrative approach to working with numbers based on a Freirean principles of raising critical consciousness and challenging social injustice. Teaching on research methods units at both undergraduate and postgraduate level, he has also successfully supervised a number of PhD students through to completion. In addition to co-authoring of a number of journal articles on pedagogic approaches to teaching statistics, he has written on ethnographies of men's health.
Dr John E. Goldring is the Co-Director of the Q-Step Centre at Manchester Metropolitan University, one of 15 centres across the UK to receive funding to promote the development of quantitative methods teaching across the HE sector. Joining Manchester Metropolitan University in 2004, his initial research and teaching focus was on men, masculinity and health. He started teaching statistical analysis in 2012 where he developed a narrative approach to working with numbers based on a Freirean principles of raising critical consciousness and challenging social injustice. Teaching on research methods units at both undergraduate and postgraduate level, he has also successfully supervised a number of PhD students through to completion. In addition to co-authoring of a number of journal articles on pedagogic approaches to teaching statistics, he has written on ethnographies of men's health.
Content
Introducing Descriptive and Exploratory Statistics
Finding Data to Describe
Measure everything - Learn something - Answer nothing: An exploration into variables and types of Measurement
I am not a number, I am a categorical variable
I like being average, I am an interval variable
Visualising Our Data
The story waiting to be told
Finding Data to Describe
Measure everything - Learn something - Answer nothing: An exploration into variables and types of Measurement
I am not a number, I am a categorical variable
I like being average, I am an interval variable
Visualising Our Data
The story waiting to be told