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"It is clear the authors have worked to write in a way that learners of all levels can understand and benefit from the content. Notations are commonly recognized, clear, and easy to follow. Figures and tables are appropriate and useful. I especially appreciate that the authors took the time not only to address important topics and steps for conducting NHST and various ANOVA designs but also to address social justice and equity issues in quantitative research as well as epistemologies and how they connect to research methods. These are important considerations and ones that are not included in many design/analysis textbooks.
This text seems to capture the elements often found in multiple, separate sources (e.g., epistemology, research design, analysis, use of statistical software, and considerations for social justice/equity) and combines them in one text. 
This is so helpful, useful, and needed!"-- Sara R. Gordon, Ph.D., Associate Professor, Center for Leadership and Learning, Arkansas Tech University, USA
"The ability to analyze data has never been more important given the volume of information available today. A challenge is ensuring that individuals understand the connectedness between research design and statistical analysis. Strunk and Mwavita introduce fundamental elements of the research process and illustrate statistical analyses in the context of research design. This provides readers with tangible examples of how these elements are related and can affect the interpretation of results.
Many statistical analysis and research design textbooks provide depth but may not situate scenarios in an applied context. Strunk and Mwavita provide illustrative examples that are realistic and accessible to those seeking a strong foundation in good research practices." -- Forrest C. Lane, Ph.D., Associate Professor and Chair, Department of Educational Leadership, Sam Houston State University, USA
"Strunk and Mwavita provide a sound introductory text that is easily accessible to readers learning applied analysis for the first time.
The chapters flow easily through traditional topics of null hypothesis testing and p-values. The chapters include hand calculations that assist students in understanding where the variance is and case studies at the end to develop writing skills related to each analysis. In addition, software is integrated toward the end of the chapters after readers have seen and learned to interpret the techniques by hand. Finally, the length of the book is more manageable for readers as a first introduction to educational statistics." -- James Schreiber, Ph.D., Professor, School of Nursing, Duquesne University, USA

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