** SECOND EDITION NOW AVAILABLE: SEE http://amzn.to/2uMPIbJ ** 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. 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. 5th Update: August 1, 2016
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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.
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Paperback. Condizione: Good. Designed for beginning and intermediate data scientists, graduate students beginning 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, then computationally (using the R Statistical Software) so that readers can see exactly how the computations are performed. Each technique is framed within an easy-to-apply 7 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 you get started. If you have some experience already, this book will make you more productive and enhance your understanding of foundational statistical concepts including one and two-sample t-tests, paired t-test, one and two proportion z-test, Chi-square test of independence, one-way ANOVA, and inference for linear regression. Codice articolo CIN0692339426G
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8Vo Softcover. Condizione: Very Good. 3rd. 504p. White pages are unmarked. Binding is tight, spine is unbroken. Covers are glossy with minimal wear. Supplements not included. Codice articolo 92491
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