This book presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool of analyzing research data. The author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the datas contextual situation.  The book presents the entire data analysis process as a cyclical, multi-phase process and addresses the processes of exploratory analysis, decision-making for performing parametric or non-parametric analysis, and practical significance determination.  Filling the gap in quantitative data analysis literature, this book focuses on teaching the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests.  With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis.  These practical approaches to quantitative data analysis illustrate how to use research data analysis methods and techniques to reveal the underlying patterns, trends, and relationships between the variables; contextualize the data to a research situation; connect the data with the appropriate test; and draw valid conclusions from it.  This book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts, allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications.  This book also features useful marginal notes to explain key ideas and/or data analysis decision points.

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