Statistics with R - by Jenine K Harris (Paperback)
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<p/><br></br><p><b> About the Book </b></p></br></br>Drawing on examples from across the social and behavioral sciences, <strong>Statistics with R: Solving Problems Using Real-World Data</strong> by Jenine K. Harris introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world's tricky problems faced by the R Team characters. Inspired by the programming group R Ladies, the R Team works together to master the skills of statistical analysis and data visualization to untangle real-world, messy data using R. The storylines draw students into investigating contemporary issues such as marijuana legalization, voter registration, and the opioid epidemic, and lead them step-by-step through full-color illustrations of R statistics and interactive exercises.<p/><br></br><p><b> Book Synopsis </b></p></br></br>Drawing on examples from across the social and behavioral sciences, <strong>Statistics with R: Solving Problems Using Real-World Data</strong> by Jenine K. Harris introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world's tricky problems faced by the R Team characters. Inspired by the programming group R Ladies, the R Team works together to master the skills of statistical analysis and data visualization to untangle real-world, messy data using R. The storylines draw students into investigating contemporary issues such as marijuana legalization, voter registration, and the opioid epidemic, and lead them step-by-step through full-color illustrations of R statistics and interactive exercises.<p/><br></br><p><b> Review Quotes </b></p></br></br><br><p><strong>Statistics With R</strong> is easily the most accessible and almost fun introduction to statistics and R that I have read. Even the most hesitant student is likely to embrace the material with this text.</p> <br/>--David A.M. Peterson<br><br><p>A unique introduction to statistics using characters in a storyline who are themselves learning how to solve real case studies using the R programming language. The first statistics textbook of its kind!</p> <br/>--Patrick Bolger<br><br><p>Allowing students to see how statistics is actually relevant to them through guided stories is a priceless experience. This text provides cross-cutting skills in R programming that students can take away with them for their CVs/résumés and career development.</p> <br/>--Benjamin Becerra<br><br><p>There are many good statistics textbooks on the market- and there are equally good books that teach R; there are very few that do both. This book fills this gap. Students who use this text will benefit not only from having a top-notch stats textbook, but a great resource for how to conduct their analysis in R.</p> <br/>--Jonathan Hack<br><br><p>This is a wonderful, innovative statistics text that integrates R coding into learning about quantitative methods. The highly engaging lessons walk students through each stage of the analytical process and teach students how to perform a statistical analysis, including the presentation of results in graphical form, using code.</p> <br/>--Jennifer Bachner<br><br><p>This is an engaging textbook for learning statistics and R at the same time.</p>--Yi Shao<br><br><p>This is an entertaining and unorthodox text that explains statistical concepts in a way that engages students and rewards them for achievements. As useful to instructors as it is to their students. </p> <br/>--Matthew Phillips<br><br><p>This text makes the R statistics software accessible to all students by providing excellent examples and step-by-step processes. The student gains mastery over statistical analysis that can be applied to the real world.</p> <br/>--Mary A. Moore<br><br><p>Using a simple but engaging style, this textbook relies on three friendly characters to introduce and explore the most common statistical problems students will face in their career. And, as a bonus, students learn how to use and master R for analyzing and illustrating simple and complex data sets.</p> <br/>--Sylvain Fiset<br>
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