′This engagingly written and nicely opinionated book is a blend of friendly introduction and concisely applicable detail. No-one can recall every statistical formula, but if they have this book they will know where to look′ - Professor Jon May, University of Plymouth ′This is one of the best books I have come across for teaching introductory statistics. The illustrative examples are engaging and often humorous and the explanations of ′difficult′ concepts are written in a wonderfully clear and intuitive way′ - Nick Allum, University of Essex Selected as an Outstanding Academic Title by Choice Magazine, January 2010 First (and Second) Steps in Statistics, Second Edition provides a clear and concise introduction to the main statistical procedures used in the social and behavioural sciences and is perfect for the statistics student starting their journey. The rationale and procedure for analyzing data are presented through exciting examples with an emphasis on understanding rather than computation. It is ideally suited for introductory courses in statistics given its gentle beginning, yet progressive treatment of topics. In addition to descriptive statistics, graphs, t-tests, oneway ANOVAs, Chi-square, and simple linear regression, this Second Edition now includes some new, more advanced topic areas as well as a host of additional examples to help students confidently progress through their studies and apply the techniques in lab work, reports and research projects. Key features of this new edition: - the reoganization of the first three chapters giving more attention to univariate statistics and providing more examples to work through at this level - more advanced ′second step′ content has been added on factorial ANOVA and multiple regression - the robust methods chapter from the first edition is now spread throughout the book, and is linked with common teaching practices. - many more examples have been added to enhance the book′s practical potential. - a host of exercises as well as further reading sections at the end of every chapter. An accompanying Web page includes information for each chapter using the statistical packages SPSS and R.

First Steps in Research and Statistics is a new, very accessible approach to learning about quantitative methods. No previous knowledge or experience is assumed and every stage of the research process is covered. Key topics include: * Formulating your research questions * How to choose the right statistical test for your research design * Important research issues, such as questionnaire design, ethics, sampling, reliability and validity * Conducting simple statistics to explore relationships and differences in your data * Using statistics to explore relationships and differences in your data * Writing up your research report and presenting statistics Simple and helpful worksheets and flow diagrams guide you through the research stages. Each chapter contains exercises with answers to check whether you've understood.

Carol S. Parke's Essential First Steps to Data Analysis: Scenario-Based Examples Using SPSS provides instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Such preparation may involve data management and manipulation tasks, data organization, structural changes to the data files, or conducting preliminary analysis. Twelve research-based scenarios are used to present the content. Each scenario tells the "story" of a researcher who thoroughly examined their data and the decisions they made along the way. The scenario begins with a description of the researcher's study and his/her data file(s), then describes the issues the researcher must address, explains why they are important, shows how SPSS was used to address the issues and prepare data, and shares the researcher's reflections and any additional decision-making. Finally, each scenario ends with the researcher's written summary of the procedures and outcomes from the initial data preparation or analysis.

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Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

This supplementary book for the social, behavioral, and health sciences helps readers with no prior knowledge of IBM® SPSS® Statistics, statistics, or mathematics learn the basics of SPSS. Designed to reduce fear and build confidence, the book guides readers through point-and-click sequences using clear examples from real scientific research and invites them to replicate the findings. Relevant outcomes are provided for reference, and exercises at the end of Chapters 2 – 5 provide additional practice. After reading the book and using the program, readers will come away with a basic knowledge of the most commonly used procedures in statistics.

The purpose of this book is to provide instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Preparation may involve data management and manipulation tasks, data organization, structural changes to data files, or conducting preliminary analysis such as examining the scale of a variable, the validity of assumptions or the nature and extent of missing data. The oresultso from these essential first steps can also help guide a researcher in selecting the most appropriate statistical tests for his/her study. The book is intended to serve as a supplemental text in statistics or research courses offered in graduate programs in education, counseling, school psychology, behavioral sciences, and social sciences as well as undergraduate programs that contain a heavy emphasis on statistics. The content and issues covered are also beneficial for faculty and researchers who are knowledgeable about research design and able to use a statistical software package, but are unsure of the first steps to take with their data. Increasingly, faculty are forming partnerships with schools, clinics, and other institutions to help them analyze data in their extensive databases. This book can serve as a reference for helping them get existing data files in an appropriate form to run statistical analysis. This book is not a replacement for a statistics textbook. It assumes that readers have some knowledge of basic statistical concepts and use of statistical software, or that they will be learning these concepts and skills concurrently throughout the course. SPSS was chosen to illustrate the preparation, evaluation, and manipulation of data. However, students or researchers who do not use SPSS will benefit from the content since the overall structure and pedagogical approach of the book focuses heavily on the data issues and decisions to be made.

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Research Basics: Design to Data Analysis in Six Steps offers a fresh and creative approach to the research process based on author James V. Spickard’s decades of teaching experience. Using an intuitive six-step model, readers learn how to craft a research question and then identify a logical process for answering it. Conversational writing and multi-disciplinary examples illuminate the model’s simplicity and power, effectively connecting the “hows” and “whys” behind social science research. Students using this book will learn how to turn their research questions into results.

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.