Taking the Fear Out of Data Analysis:Completely Revised, Significantly Extended and Still Fun

by: Adamantios Diamantopoulos (Author),Bodo B. Schlegelmilch(Author),Georgios Halkias(Author)

Publisher: Edward Elgar Publishing
Edition:Expanded

Publication Date: February 10, 2023

Language: English

Print Length: 346 pages

ISBN-10: 1803929839

ISBN-13: 9781803929835

Book Description

Taking the Fear Out of Data Analysis provides readers with the necessary knowledge and skills to understand, perform, and interpret quantitative data analysis effectively. Acknowledging that people often dislike statistics and quantitative methods, this book illustrates that statistical reasoning can be a fun and intuitive part of our lives.Key Features:Split into three sections covering how to understand data, preparing data for analysis and carrying out the analysisBlends theory with practical examples in a logical and straightforward manner to guide readers in making sense of statistical inferenceOffers universal knowledge that can be applied to a variety of software applications with limited technical complexity to aid the leaing processShort and concise chapters focusing on the essence of the topics covered, such as analytical techniques that are typically used in behavioral and social science researchSignificantly revised and updated, this textbook is an essential text for both undergraduate and postgraduate students in fields such as information systems, inteational business and marketing. It will also be beneficial for practitioners involved in data science, data analytics, and market research.
Taking the Fear Out of Data Analysis provides readers with the necessary knowledge and skills to understand, perform, and interpret quantitative data analysis effectively. Acknowledging that people often dislike statistics and quantitative methods, this book illustrates that statistical reasoning can be a fun and intuitive part of our lives.Key Features:Split into three sections covering how to understand data, preparing data for analysis and carrying out the analysisBlends theory with practical examples in a logical and straightforward manner to guide readers in making sense of statistical inferenceOffers universal knowledge that can be applied to a variety of software applications with limited technical complexity to aid the leaing processShort and concise chapters focusing on the essence of the topics covered, such as analytical techniques that are typically used in behavioral and social science researchSignificantly revised and updated, this textbook is an essential text for both undergraduate and postgraduate students in fields such as information systems, inteational business and marketing. It will also be beneficial for practitioners involved in data science, data analytics, and market research.

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