Beyond Basic Statistics PDF Download

Author: Kristin H. Jarman
Publisher: John Wiley & Sons
ISBN: 1118856120
Category : Mathematics
Languages : en
Pages : 200

View

Book Description
Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques. Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life’s important questions. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features: Plentiful examples throughout aimed to strengthen readers’ understanding of the statistical concepts and methods A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression A case study in each chapter that illustrates the use of the presented techniques Highlights of well-known shortcomings that can lead to false conclusions An introduction to advanced techniques such as validation and bootstrapping Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.

Author: Thomas J. Linneman
Publisher: Taylor & Francis
ISBN: 1136900381
Category : Mathematics
Languages : en
Pages : 574

View

Book Description
"With just the right level of detail, and a graphically innovative approach, this book carefully guides students through the statistical techniques they will encounter in the real world. The basics, plus multiple regression, interaction effects, logistic regression, non-linear effects, all covered in a non-intimidating way for your students. The book uses three datasets throughout: General Social Survey, American National Election Studies, World Values Survey, and includes SPSS demonstrations at the end of each chapter. Most of your students will likely take only one stats course and use only one stats book in their college careers. This one innovatively equips them for their worlds ahead, regardless of the career paths they follow."--Page [i].

Author: Rupert G. Miller, Jr.
Publisher: CRC Press
ISBN: 9780412070112
Category : Mathematics
Languages : en
Pages : 340

View

Book Description
Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator. This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests. Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.

Author: Benjamin Miller
Publisher: Allyn & Bacon
ISBN:
Category : Juvenile Nonfiction
Languages : en
Pages : 202

View

Book Description
A practical introduction to terms, concepts, and processes of data analysis, introducing operations common to all statistical software. This book goes beyond basic research methods and statistics, and discusses actually working with data, including data entry, data cleaning, finding errors, organizing data, transforming variables, and combining and aggregating data sets. It provides a useful vocabulary for thinking and talking about data and demystifies statistical software by showing readers how to think about data from the computer's perspective. People with an interest in research methods, experimental methodology, and statistics in the fields of psychology, sociology, and social work.

Author: Geoff Cumming
Publisher: Routledge
ISBN: 1317483375
Category : Psychology
Languages : en
Pages : 595

View

Book Description
This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.

Author: Deborah G. Mayo
Publisher: Cambridge University Press
ISBN: 1108563309
Category : Mathematics
Languages : en
Pages : 503

View

Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617

View

Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Author: Kristin H. Jarman
Publisher: John Wiley & Sons
ISBN: 1118411315
Category : Mathematics
Languages : en
Pages : 192

View

Book Description
A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.

Author: Lee Panas
Publisher: Lulu.com
ISBN: 0557312248
Category : Sports & Recreation
Languages : en
Pages : 153

View

Book Description
Over the past few decades, a multitude of advanced hitting, pitching, fielding and base running measures have been introduced to the baseball world. This comprehensive sabermetrics primer will introduce you to these new statistics with easy to understand explanations and examples. It will illustrate the evolution of statistics from simple traditional measures to the more complex metrics of today. You will learn how all the statistics are connected to winning and losing games, how to interpret them, and how to apply them to performance on the field. By the end of this book, you will be able to evaluate players and teams through statistics more thoroughly and accurately than you could before.

Author: Robert de Vries
Publisher: Bloomsbury Publishing
ISBN: 1350314374
Category : Social Science
Languages : en
Pages : 228

View

Book Description
Awarded the 2019 Most Promising New Textbook Award by the Textbook & Academic Authors Association. This accessible and entertaining new textbook provides students with the knowledge and skills they need to understand the barrage of numbers encountered in their everyday lives and studies. Almost all the statistics in the news, on social media or in scientific reports are based on just a few core concepts, including measurement (ensuring we count the right thing), causation (determining whether one thing causes another) and sampling (using just a few people to understand a whole population). By explaining these concepts in plain language, without complex mathematics, this book prepares students to meet the statistical world head on and to begin their own quantitative research projects. Ideal for students facing statistical research for the first time, or for anyone interested in understanding more about the numbers in the news, this textbook helps students to see beyond the headlines and behind the numbers.