Introductory Statistics Using R: An Easy Approach

Finally, a textbook that makes it simple to teach and learn introductory statistics using the R software! Herschel Knapp′s Introductory Statistics Using R: An Easy Approach is a jargon-free guide to real-world statistics designed to concisely answer three important questions: Which statistic should I use? How do I run the analysis? How do I document the results? Practical examples presented throughout the text with exercises at the end of each chapter build proficiency through hands-on learning. The student website includes datasets, prepared R code for each statistic in the R Syntax Guide, and tutorial videos. As well as learning statistics, with this text students learn how to convert numeric results into clear, publishable documentation.

Table of Contents:
Preface Acknowledgements About the Author Part I: Statistical Foundation Chapter 1: Research Principles Overview – Research Principles Rationale for Statistics Levels of Measure and Types of Variables Control and Treatment Groups Random Assignment Research Question and Hypothesis Formulation Asking and Answering Research Questions Good Common Sense Key Concepts Practice Exercises Chapter 2: Sampling Overview – Sampling Sampling Rationale Sampling Terminology Representative Sample Probability Sampling Nonprobability Sampling Sampling Bias Optimal Sample Size Good Common Sense Key Concepts Practice Exercises Chapter 3: Getting Started In R Overview – R And Rstudio Setting Up Your RStudio Cloud Account R Syntax Guide Loading Packages Dataset Structure Codebook Uploading a Dataset to R Data File Types First Statistical Run Variable References Exporting Results Copying Graphs Shortcuts Clear the Console Window Doing Math in R Data Order Doesn’t Matter Processing Your Own Data Logging Off Good Common Sense Key Concepts Practice Exercises Part II: Statistical Tests Chapter 4: Descriptive Statistics Overview – Descriptive Statistics Descriptive Statistics in Context Descriptive Statistics for Continuous and Categorical Variables Descriptive Statistics: Continuous Variables (Score) Descriptive Statistics: Categorical Variables (Hand) Managing Data Managing Plots Moving Forward Good Common Sense Key Concepts Practice Exercises Chapter 5: t Test and Welch Two Sample t Test Overview – t Test t Tests and Welch Two Sample t Tests in Context Example Type I and Type II Errors Good Common Sense Key Concepts Practice Exercises Chapter 6: ANOVA – Tukey Test and Wilcoxon Multiple Pairwise Comparisons Test Overview – ANOVA Test ANOVA Tests in Context Layered Learning Example Good Common Sense Key Concepts Practice Exercises Chapter 7: Paired t Test and Paired Wilcoxon Test Overview – Paired t Test Paired t Tests and Paired Wilcoxon Tests in Context Layered Learning Example Good Common Sense Key Concepts Practice Exercises Chapter 8: Correlation – Pearson Test and Spearman Test Overview – Pearson Test Correlation in Context More About Correlation Example Correlation Versus Causation Good Common Sense Key Concepts Practice Exercises Chapter 9: Chi-Square Overview – Chi-Square Test Chi-Square Tests in Context Example Good Common Sense Key Concepts Practice Exercises Glossary Index

About the Author :
Herschel Knapp, PhD, MSSW, has more than 30 years of experience as a health care professional in a variety of domains. In addition to his clinical work as a psychotherapist, primarily in hospital set­tings, he has provided project management for innovative interventions designed to improve the quality of patient care via multisite, health science implementations. He teaches master’s and doctoral courses at Yeshiva University; he has also taught at the University of California, Los Angeles, University of Southern California, California State University, Los Angeles, and California State, San Bernardino.  Dr. Knapp has served as the lead statistician on a lon­gitudinal cancer research project and managed the program evaluation metrics for a multisite, nonprofit children’s center. His clinical work includes emergency/trauma therapy in hospital settings. Dr. Knapp has developed and implemented innovative tele­health systems, using videoconferencing technology to facilitate optimal health care service delivery to remote patients and to coordinate specialty consultations among health care providers, including interventions to diagnose and treat people with HIV and hepatitis, with special outreach to the homeless. He created and implemented a nurse research mentorship program, providing research and analytic education, enabling nurses to design, implement, analyze, and publish the results of their quality improvement projects. Dr. Knapp has published numerous articles in peer-reviewed health science journals and serves as a peer-reviewer for more than 20 science journals. He is also the author of other textbooks, including Intermediate Statistics Using SPSS (2018), Introductory Statistics Using SPSS (2nd ed., 2017), Practical Statistics for Nursing Using SPSS (2017), Therapeutic Communication: Developing Professional Skills (2nd ed., 2014), and Introduction to Social Work Practice: A Practical Workbook (2010).

Review :
Finally! A truly straightforward introduction to statistics and R. Writing is approachable, clear, and concise. Students and those interested in getting started with R will find this textbook extremely useful and approachable. This is an essential guide for new R instructors and students aiming to proficiently grasp statistical analysis. With its clear, step-by-step approach and practical emphasis on real-world applications, this textbook empowers learners with the necessary skills to navigate statistical analysis in R with confidence. I highly recommend it! This book offers a step-by-step guide appropriate for college students new to both statistics and the statistical software R. The author magically guides us through the journey using approachable language, complemented by the activities and exercises that build on each other throughout the textbook. I know this book is the best available introductory research textbook appropriate for my students in Family and Consumer Sciences. I highly appreciate this amazing book. It provides a crucial understanding for students of the importance and application of statistical tools in practice. Part 1: Statistical Foundation sets the book apart, as it uniquely emphasizes the foundational reasons behind using statistical methods, something not commonly found in other texts. An essential guide for learning statistics with R, this book offers clear explanations, practical exercises, and valuable multimedia resources, making complex concepts accessible and engaging for students of all levels. This text serves not only as a process guide for utilizing R for statistical analyses, but it also contains a very clear presentation of research methods, and the foundational knowledge needed to understand the analyses. This text is a helpful tool for teaching and learning statistics with R. This is an effective, easy to use textbook that guides students not only through the fundamentals of statistics, but also how to run the analysis and interpret the outputs. It is rare that a textbook presents both parametric and non-parametric approaches to basic statistics. The information presented in this textbook is accessible and adds the skill of using R to students resumes.