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.
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 £1.15 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.
Inhaltsangabe
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
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
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