Field masterfully weaves in a unique, action-packed story starring Zach, a character who thinks like a student, processing information, and the challenges of understanding it, in the same way a statistics novice would.
Illustrated with stunning graphic novel-style art and featuring Socratic dialogue, the story captivates readers as it introduces them to concepts, eliminating potential statistics anxiety. The book assumes no previous statistics knowledge nor does it require the use of data analysis software. It covers the material you would expect for an introductory level statistics course that Field''s other books Discovering Statistics Using IBM SPSS Statistics and Discovering Statistics Using R only touch on, but with a contemporary twist, laying down strong foundations for understanding classical and Bayesian approaches to data analysis.
In doing so, it provides an unrivalled launch pad to further study, research, and inquisitiveness about the real world, equipping students with the skills to succeed in their chosen degree and which they can go on to apply in the workplace. Prior to the revolution, Elpis citizens were unable to see their flaws and limitations, believing themselves talented and special.
This led to a self-absorbed society in which hard work and the collective good were undervalued and eroded. To combat this, Professor Milton Grey invented the reality prism, a hat that allowed its wearers to see themselves as they really were - flaws and all. Faced with the truth, Elpis citizens revolted and destroyed and banned all reality prisms. The Mysterious Disappearance Zach and Alice are born soon after all the prisms have been destroyed. Zach, a musician who doesn''t understand science, and Alice, a geneticist who is also a whiz at statistics, are in love.
One night, after making a world-changing discovery, Alice suddenly disappears, leaving behind a song playing on a loop and a file with her research on it. Statistics to the Rescue! Sensing that she might be in danger, Zach follows the clues to find her, as he realizes that the key to discovering why Alice has vanished is in her research. He must learn statistics and apply what he learns in order to overcome a number of deadly challenges and find the love of his life.
As Zach and his pocket watch, The Head, embark on their quest to find Alice, they meet Professor Milton Grey and attractive Celia, battle zombies, cross a probability bridge, and encounter Jig:Saw, a mysterious corporation that might have something to do with Alice''s disappearance Author News "Eight years ago I had the idea to write a fictional story through which the student learns statistics via a shared adventure with the main character Video Links Go behind the scenes and learn more about the man behind the book: Watch Andy talk about why he created a statistics book using the framework of a novel and illustrations by one of the illustrators for the show, Doctor Who.
See more videos on Andy''s YouTube channel. The Fourth Edition focuses on providing essential content updates, better accessibility to key features, more instructor resources, and more content specific to select disciplines. It also incorporates powerful new digital developments on the textbook's companion website visit sagepub.
Students receive unlimited practice using a combination of approximately multiple choice and algorithmic questions. WebAssign provided students with instant feedback and links directly to the accompanying eBook section where the concept was covered, allowing students to find the correct solution. With QR codes included throughout the text, it's easy for students to get right to the section they need to study, allowing them to continue their study from virtually anywhere, even when they are away from thier printed copy of the text.
Visit the publisher's website to preview the MobileStudy site. Education and Sport Sciences instructor support materials with enhanced ones for Psychology, Business and Management and the Health sciences make the book even more relevant to a wider range of subjects across the social sciences and where statistics is taught to a cross-disciplinary audience.
An enhanced Companion Website visit the publisher's website for more information offers a wealth of material that can be used in conjunction with the textbook, including: PowerPoints Testbanks Answers to the Smart Alex tasks at the end of each chapter Datafiles for testing problems in SPSS Flashcards of key concepts Self-assessment multiple-choice questions Online videos of key statistical and SPSS procedures. It provides a complete map of the entire process beginning with how to get ideas about research, how to refine your research question and the actual design of the experiment, leading on to statistical procedure and assistance with writing up of results.
While many books look at the fundamentals of doing successful experiments and include good coverage of statistical techniques, this book very importantly considers the process in chronological order with specific attention given to effective design in the context of likely methods needed and expected results.
Without full assessment of these aspects, the experience and results may not end up being as positive as one might have hoped. Ample coverage is then also provided of statistical data analysis, a hazardous journey in itself, and the reporting of findings, with numerous examples and helpful tips of common downfalls throughout.
Combining light humour, empathy with solid practical guidance to ensure a positive experience overall, Designing and Reporting Experiments will be essential reading for students in psychology and those in cognate disciplines with an experimental focus or content in research methods courses. The text includes topics typically covered in introductory textbooks: probability, descriptive statistics, visualization, comparisons of means, tests of association, correlations, OLS regression, and power analysis.
However, it also transcends other books at this level by covering topics such as bootstrapping and an introduction to R, for those who are novices to this powerful tool. In a straightforward and easy-to-understand format, the authors provide readers with a plethora of freely available and robust resources and examples that are applicable to a wide variety of behavioral and social science disciplines, including social work, psychology, and physical and occupational therapy.
The book is a must-read for all professors and students endeavoring to learn basic statistics. Author : Ryan A. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with.
The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Author : Ray W. Cooksey Publisher: Springer Nature ISBN: Category: Mathematics Page: View: Read Now » This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them.
This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts.
It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
Author : A. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R.
The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs.
Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises with solutions included in the back of the book , and references and related readings.
Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets.
The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data.
Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period.
Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. Loved each and every part of this book.
I will definitely recommend this book to science, mathematics lovers. Your Rating:. Your Comment:. Read Online Download. Great book, Discovering Statistics Using R pdf is enough to raise the goose bumps alone.
Add a review Your Rating: Your Comment:. How to Lie with Statistics by Darrell Huff.
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