Author: Peter Dalgaard
Publisher: Springer Science & Business Media
View: 6847This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Author: Sheldon M. Ross
Publisher: Academic Press
View: 7554Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises. Includes new section on Pareto distribution and the 80-20 rule, Benford’s law, odds, joint distribution and correlation, logistic regression, A-B testing, and examples from the world of analytics and big data Comprehensive edition that includes the most commonly used statistical software packages (SAS, SPSS, Minitab), ISM, SSM, and an online graphing calculator manual Presents a unique, historical perspective, profiling prominent statisticians and historical events to motivate learning by including interest and context Provides exercises and examples that help guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud
Author: Prem S. Mann
Publisher: John Wiley & Sons
View: 1385When it comes to learning statistics, Mann delivers the information that business professionals need. The new edition incorporates the most up-to-date methods and applications to present the latest information in the field. It focuses on explaining how to apply the concepts through case studies and numerous examples. Data integrated throughout the chapters come from a wide range of disciplines and media sources. Over 200 examples are included along with marginal notes and step-by-step solutions. The Decide for Yourself feature also helps business professionals explore real-world problems and solutions.
Author: R. E. Parker,Reginald Ernest Parker
Publisher: Cambridge University Press
View: 325This introductory text presents the use of statistical methods as an integral part of biological investigation, yet one whose superficial complexities have deterred many biologists from using them. The author argues that the difficulties, such as they are, do not lie in mathematical manipulation, but in grasping a few simple, but unfamiliar concepts. He emphasizes the need for precisely defining problems and for careful selection of the most appropriate methods - a wide range of which are described and illustrated. Each chapter ends with a set of problems which are intended to help the student gain practical experience. No previous knowledge is assumed, and the student is encouraged to develop a competent and critical approach to analysing numerical data. In this second edition, the scope of the book has been extended, problems have been solved in a more satisfactory way, and a greater number of illustrative examples have been added.
Author: John Verzani
Publisher: CRC Press
View: 4408The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Author: Textbook Equity Edition
View: 9695Introductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them.
A Conceptual Approach Using R
Author: William B. Ware,John M. Ferron,Barbara Manning Miller
View: 609"This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. The focus throughout is more on conceptual understanding, the attainment of statistical literacy and thinking than on learning a set of tools and procedures. An organizational scheme built around common issues and problems rather than statistical techniques allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Whenever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following. Conceptual Focus--The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures. Problems and Cases--Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output. Continuity of Examples--A master data set containing nearly all of the data used in the book's examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text. Companion Website--A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises. Field Tested--The manuscript has been field tested for three years at two leading institutions"--
Author: Joan Welkowitz,Barry H. Cohen,Robert B. Ewen
Publisher: John Wiley & Sons
View: 4892A comprehensive and user-friendly introduction to statistics-now revised and updated Introductory Statistics for the Behavioral Sciences has had a long and successful history and is a popular and well-respected statistics text. Now in its sixth edition, the text has been thoroughly revised to present all the topics students in the behavioral sciences need in a uniquely accessible format that aids in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences. Using a continuous narrative that explains statistics and tracks a common data set throughout, the authors have developed an innovative approach that makes the material unintimidating and memorable, providing a framework that connects all of the topics in the text and allows for easy comparison of different statistical analyses. New features in this Sixth Edition include: * Different aspects of a common data set are used to illustrate the various statistical methods throughout the text, with an emphasis on drawing connections between seemingly disparate statistical procedures and formulas * Computer exercises based on the same large data set and relevant to that chapter's content. The data set can be analyzed by any available statistical software * New "Bridge to SPSS" sections at the end of each chapter explain, for those using this very popular statistical package, how to perform that chapter's statistical procedures by computer, and how to translate the output from SPSS * New chapters on multiple comparisons and repeated-measures ANOVA
Use and Interpretation, Fourth Edition
Author: George A. Morgan,Nancy L. Leech,Gene W. Gloeckner,Karen C. Barrett
Publisher: Taylor & Francis
View: 4717"Designed to help students analyze and interpret research data using IBM SPSS, this book describes the use of statistics in user-friendly, non-technical language to show readers how to choose the appropriate statistic based on the design, interpret output, and write about the results. The authors prepare readers for all of the steps in the research process, from design and data collection, to writing about the results. Discussions of writing about outputs, data entry and checking, reliability assessment, testing assumptions, and computing descriptive and inferential parametric and nonparametric statistics are included. SPSS syntax, along with the output, is provided for those who prefer this format"--Provided by publisher.
Theory, Exercises and Solutions
Author: Jan Ubøe
Category: Business & Economics
View: 3954This textbook discusses central statistical concepts and their use in business and economics. To endure the hardship of abstract statistical thinking, business and economics students need to see interesting applications at an early stage. Accordingly, the book predominantly focuses on exercises, several of which draw on simple applications of non-linear theory. The main body presents central ideas in a simple, straightforward manner; the exposition is concise, without sacrificing rigor. The book bridges the gap between theory and applications, with most exercises formulated in an economic context. Its simplicity of style makes the book suitable for students at any level, and every chapter starts out with simple problems. Several exercises, however, are more challenging, as they are devoted to the discussion of non-trivial economic problems where statistics plays a central part.
The Logic and the Methods
Author: Gustav Levine
Publisher: Academic Press
View: 362Introductory Statistics for Psychology: The Logic and the Methods presents the concepts of experimental design that are carefully interwoven with the statistical material. This book emphasizes the verbalization of conclusions to experiments, which is another means of communicating the reasons for statistical analyses. Organized into 17 chapters, this book begins with an overview of alternative ways of stating the conclusions from a significant interaction. This text then presents the analysis of variance and introduces the summation sign and its use. Other chapters consider frequency distribution as any presentation of data that offers the frequency with which each score occurs. This book discusses as well the differences in and among people, which are a constant source of variability in test scores, and in most other measurements of people. The final chapter deals with the working knowledge of arithmetic and elementary algebra. This book is a valuable resource for students and psychologists.
A Short Guide to Introductory Statistics in the Social Sciences
Author: Roberta Garner
Publisher: University of Toronto Press
View: 1001"This is a great book for social science students. Clearly written, with many examples, Garner certainly makes learning and teaching introductory statistics a joy!" - Nikolaos Liodakis, Wilfrid Laurier University
A Resampling Perspective
Author: Peter C. Bruce
Publisher: John Wiley & Sons
View: 5280Concise, thoroughly class-tested primer that features basicstatistical concepts in the concepts in the context of analytics,resampling, and the bootstrap A uniquely developed presentation of key statistical topics,Introductory Statistics and Analytics: A ResamplingPerspective provides an accessible approach to statisticalanalytics, resampling, and the bootstrap for readers with variouslevels of exposure to basic probability and statistics. Originallyclass-tested at one of the first online learning companies in thediscipline, www.statistics.com, the book primarily focuses onapplications of statistical concepts developed via resampling, witha background discussion of mathematical theory. This featurestresses statistical literacy and understanding, which demonstratesthe fundamental basis for statistical inference and demystifiestraditional formulas. The book begins with illustrations that have the essentialstatistical topics interwoven throughout before moving on todemonstrate the proper design of studies. Meeting all of theGuidelines for Assessment and Instruction in Statistics Education(GAISE) requirements for an introductory statistics course,Introductory Statistics and Analytics: A ResamplingPerspective also includes: Over 300 “Try It Yourself” exercises andintermittent practice questions, which challenge readers atmultiple levels to investigate and explore key statisticalconcepts Numerous interactive links designed to provide solutions toexercises and further information on crucial concepts Linkages that connect statistics to the rapidly growing fieldof data science Multiple discussions of various software systems, such asMicrosoft Office Excel®, StatCrunch, and R, to develop andanalyze data Areas of concern and/or contrasting points-of-view indicatedthrough the use of “Caution” icons Introductory Statistics and Analytics: A ResamplingPerspective is an excellent primary textbook for courses inpreliminary statistics as well as a supplement for courses inupper-level statistics and related fields, such as biostatisticsand econometrics. The book is also a general reference for readersinterested in revisiting the value of statistics.
Author: M.H. Quenouille
View: 9366Introductory Statistics is an elementary non-mathematical manual on statistics and provides a connected account of the more common statistical tests. It is divided into two parts: the first part introduces the reader to elementary applications of statistical methods and the line of reasoning involved in their use, and the second part covers elementary parts of statistical theory and more advanced applications. This book consists of nine chapters and opens with a discussion on the presentation of sets of measurements, touching on topics such as sampling, grouping, measures of spread, and standard deviation. The following chapters deal with normal distribution and its applications; comparison of two or several sets of measurements; attributes and comparison of proportions; and interrelations of sets of measurements. Concomitant observations are also considered, along with transformations and non-normal distributions. The final chapter is devoted to sampling methods, including the ratio method and the regression method. This monograph is written primarily for students of statistics and aims to help research workers gain a fuller understanding of the methods used in the analysis of their results.
Author: Herschel Knapp
Publisher: SAGE Publications
Category: Social Science
View: 2602The updated Second Edition of Herschel Knapp’s friendly and practical introduction to statistics shows students how to properly select, process, and interpret statistics without heavy emphasis on theory, formula derivations, or abstract mathematical concepts. Each chapter is structured to answer questions that students most want answered: What statistical test should I use for this situation? How do I set up the data? How do I run the test? How do I interpret and document the results? Online tutorial videos, examples, screenshots, and intuitive illustrations help students "get the story" from their data as they learn by doing, completing practice exercises at the end of each chapter using prepared downloadable data sets.