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Statistics (The Easier Way) with R: an informal text on applied statistics, by Nicole M. Radziwill
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Want to learn R, statistics, or data analysis? Become successful fast with this unique book, which takes the approach of solving all problems analytically (using equations) before solving them using the R statistical software. (INSTRUCTORS: Course Materials are available.) This combined approach is embedded within a 12-step process for hypothesis testing, which will make statistical inference clearer than ever, while giving you a structured approach for presenting your research results.Most books about applied statistics just focus on the math and theory. Most books about the R statistical software package just focus on executing tests. But in Statistics (The Easier Way) with R, you'll see exactly what computations R is doing under the surface, helping you become a more skilled investigator and data analyst.In addition to being a great introductory text for learning applied statistics or R, Statistics (The Easier Way) with R is also suitable as a supplement for any undergraduate course in introductory or applied statistics, high school AP statistics, or Six Sigma Green Belt and Six Sigma Black Belt candidates. Errata and other notes from first printing are available at qualityandinnovation.com/errata/.
- Sales Rank: #54624 in Books
- Published on: 2015-03-21
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.21" w x 7.50" l, 2.01 pounds
- Binding: Paperback
- 536 pages
From the Inside Flap
4th Update: December 5, 2015
From the Back Cover
Designed for beginning and intermediate data scientists, graduate students starting research, undergraduate students taking a first or second applied statistics class, quality improvement professionals, and consultants, this unique book provides an integrated treatment of statistical inference techniques in data analysis. Each example is solved analytically (using equations), and then also in the R software so that readers can see exactly how the computations are performed. Each technique is framed within an easy-to-apply 12-step methodology that will make planning and presenting research a breeze. If you're new to statistics, data science, or R, this book will help get you started. If you have some experience already, this book will make you more productive and enhance your understanding of foundational statistical concepts.
About the Author
Nicole Radziwill is an Associate Professor in the Department of Integrated Science and Technology at James Madison University (JMU), where she has been on the faculty since 2009. Nicole is also a Fellow of the American Society for Quality (ASQ), Certified by ASQ as a Manager of Quality and Organizational Excellence (CMQ/OE), and an ASQ Certified Six Sigma Black Belt (CSSBB). She served as a national Examiner for the Malcolm Baldrige National Quality Award (MBNQA) in 2009 and 2010, and has a PhD in Technology Management and Quality Systems from Indiana State University. She also has an MBA and a BS degree in Meteorology from Penn State. Nicole was recognized by Quality Progress in 2011 as one of the 40 New Voices of Quality, and serves as one of ASQ’s Influential Voices bloggers.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Numeracy starts with stats. This book provides a warm, friendly welcome.
By Ron DuPlain
This book is great! Appendix F is my favorite. It shows which statistical tests in your toolbox you should use based on the type of data and the comparison you are performing in your work. You will use the right test in your work, but perhaps more fun, you will be prepared to call out the bogus paper which uses a t-test on non-normal data. Nice use of graphics to understand the math (and even Wolfram Alpha in a few places!).
2 of 2 people found the following review helpful.
Not The Easier Way... the EASIEST Way!!!
By Joseph Straub
WOW! This book has really helped me understand R, in an easier way. I love how the book is structured like a conversation. The text anticipates what I struggle with and has the answer to what I am thinking in the next line. I also really appreciate how it explains the “behind the scenes” of R and helps you understand the formulas that are being calculated. For beginners and experts alike, I highly recommend this book to get you on track to learning the powers of R.
2 of 2 people found the following review helpful.
This book is excellent. It does what so many texts on statistics ...
By Alex
This book is excellent. It does what so many texts on statistics or R fail to do: provide an welcoming path for learning the subject. It's written with down-to-earth language, humor, and an excellent notion of how to engage her audience. Nicole guides you through various topics in practical statistical methods and how to program in R so that it's actually enjoyable instead of making it a fairly painful process like so many others do. Highly recommended.
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