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Statistics is confusing, even for smart, technically competent people. And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are: • Easy to Understand: Uses unique “graphics that teach” such as concept flow diagrams, compare-and-contrast tables, and even cartoons to enhance “rememberability.” • Easy to Use: Alphabetically arranged, like a mini-encyclopedia, for easy lookup on the job, while studying, or during an open-book exam. • Wider Scope: Covers Statistics I and Statistics II and Six Sigma Black Belt, adding such topics as control charts and statistical process control, process capability analysis, and design of experiments. As a result, this book will be useful for business professionals and industrial engineers in addition to students and professionals in the social and physical sciences. In addition, each of the 60+ concepts is covered in one or more articles. The 75 articles in the book are usually 5–7 pages long, ensuring that things are presented in “bite-sized chunks.” The first page of each article typically lists five “Keys to Understanding” which tell the reader everything they need to know on one page. This book also contains an article on “Which Statistical Tool to Use to Solve Some Common Problems”, additional “Which to Use When” articles on Control Charts, Distributions, and Charts/Graphs/Plots, as well as articles explaining how different concepts work together (e.g., how Alpha, p, Critical Value, and Test Statistic interrelate). ANDREW A. JAWLIK received his B.S. in Mathematics and his M.S. in Mathematics and Computer Science from the University of Michigan. He held jobs with IBM in marketing, sales, finance, and information technology, as well as a position as Process Executive. In these jobs, he learned how to communicate difficult technical concepts in easy - to - understand terms. He completed Lean Six Sigma Black Belt coursework at the IASSC - accredited Pyzdek Institute. In order to understand the confusing statistics involved, he wrote explanations in his own words and graphics. Using this material, he passed the certification exam with a perfect score. Those statistical explanations then became the starting point for this book.
Statistics is confusing, even for smart, technically competent people. And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are: • Easy to Understand: Uses unique “graphics that teach” such as concept flow diagrams, compare-and-contrast tables, and even cartoons to enhance “rememberability.” • Easy to Use: Alphabetically arranged, like a mini-encyclopedia, for easy lookup on the job, while studying, or during an open-book exam. • Wider Scope: Covers Statistics I and Statistics II and Six Sigma Black Belt, adding such topics as control charts and statistical process control, process capability analysis, and design of experiments. As a result, this book will be useful for business professionals and industrial engineers in addition to students and professionals in the social and physical sciences. In addition, each of the 60+ concepts is covered in one or more articles. The 75 articles in the book are usually 5–7 pages long, ensuring that things are presented in “bite-sized chunks.” The first page of each article typically lists five “Keys to Understanding” which tell the reader everything they need to know on one page. This book also contains an article on “Which Statistical Tool to Use to Solve Some Common Problems”, additional “Which to Use When” articles on Control Charts, Distributions, and Charts/Graphs/Plots, as well as articles explaining how different concepts work together (e.g., how Alpha, p, Critical Value, and Test Statistic interrelate). ANDREW A. JAWLIK received his B.S. in Mathematics and his M.S. in Mathematics and Computer Science from the University of Michigan. He held jobs with IBM in marketing, sales, finance, and information technology, as well as a position as Process Executive. In these jobs, he learned how to communicate difficult technical concepts in easy - to - understand terms. He completed Lean Six Sigma Black Belt coursework at the IASSC - accredited Pyzdek Institute. In order to understand the confusing statistics involved, he wrote explanations in his own words and graphics. Using this material, he passed the certification exam with a perfect score. Those statistical explanations then became the starting point for this book.
From 'Abcissa' to 'Zygosity determination' - this accessible introduction to the terminology of medical statistics describes more than 1500 terms all clearly explained, illustrated and defined in non-technical language, without any mathematical formulae! With the majority of terms revised and updated and the addition of more than 100 brand new definitions, this new edition will enable medical students to quickly grasp the meaning of any of the statistical terms they encounter when reading the medical literature. Furthermore, annotated comments are used judiciously to warn the unwary of some of the common pitfalls that accompany some cherished biomedical statistical techniques. Wherever possible, the definitions are supplemented with a reference to further reading where the reader may gain a deeper insight, so whilst the definitions are easily disgestible, they also provide a stepping stone to a more sophisticated comprehension. Statistical terminology can be quite bewildering for clinicians: this guide will be a lifesaver.
Succinctly explains statistical terms encountered in medicine using non-technical language, giving advice on common pitfalls in techniques.
Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.
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.
A friendly and accessible guide to psychological research methods, Your A to Z of Research Methods and Statistics in Psychology is the perfect companion to your core research methods textbook. This clear and extensive A to Z covers all the key terms and concepts you need to navigate methods and statistics in psychology with ease.
What does this p-value actually mean? And what is a significant result? This book provides a compact and comprehension-oriented introduction to inferential statistics and answers questions like these. One focus is on the logic underlying inferential statistics and hypothesis testing: Readers learn the most commonly used procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) as well as the pitfalls of data analysis, and develop the understanding necessary to interpret results correctly. The individual chapters are supplemented by concrete evaluation examples from everyday research - including exemplary implementation with the programs SPSS and R. In addition to the classic methods, cross-references to current developments in psychological methodological research are also included.This book is a translation of the original German 3rd edition of Inferenzstatistik verstehen by Markus Janczyk and Roland Pfister. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.