Statistics (The Easier Way) With R: An informal text on applied statistics and data science - Nicole M. Radziwill

Résumé :
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.

Biographie:
Nicole Radziwill is an Associate Professor in the Department of Integrated Science and Technology (ISAT) at James Madison University (JMU) in Harrisonburg, Virginia. She is a Fellow of the American Society for Quality (ASQ) and is a Certified Six Sigma Black Belt (CSSBB) and Certified Manager of Quality and Organizational Excellence (CMQ/OE). She has a Ph.D. in Quality Systems, and her research uses data science to explore Quality 4.0: quality and innovation in intelligent automation and cyber-human production systems. She is one of ASQ's Influential Voices and blogs at http://qualityandinnovation.com.