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Author: Neil A. Weiss Publisher: Pearson College Division ISBN: 9780321691224 Category : Mathematics Languages : en Pages : 759
Book Description
Weiss's Introductory Statistics, Ninth Edition is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. The text is suitable for a one- or two-semester course. Comprehensive in its coverage, Weiss's meticulous style offers careful, detailed explanations to ease the learning process. With more than 1,000 data sets and more than 2,600 exercises, most using real data, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical literacy. Introductory Statistics, Ninth Edition, contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows both the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two. This edition continues the book's tradition of being on the cutting edge of statistical pedagogy, technology, and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers, and websites. Datasets and other resources (where applicable) for this book are available here.
Author: Neil A. Weiss Publisher: Pearson College Division ISBN: 9780321691224 Category : Mathematics Languages : en Pages : 759
Book Description
Weiss's Introductory Statistics, Ninth Edition is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. The text is suitable for a one- or two-semester course. Comprehensive in its coverage, Weiss's meticulous style offers careful, detailed explanations to ease the learning process. With more than 1,000 data sets and more than 2,600 exercises, most using real data, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical literacy. Introductory Statistics, Ninth Edition, contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows both the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two. This edition continues the book's tradition of being on the cutting edge of statistical pedagogy, technology, and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers, and websites. Datasets and other resources (where applicable) for this book are available here.
Author: Stephen Kokoska Publisher: Macmillan ISBN: 1429242817 Category : Mathematics Languages : en Pages : 133
Book Description
This Guide offers students explanations of crucial concepts in each section of IPS, plus detailed solutions to key text problems and stepped-through models of important statistical techniques.
Author: Prem S. Mann Publisher: Wiley ISBN: 9781118504109 Category : Mathematics Languages : en Pages : 0
Book Description
Introductory Statistics, 8th Edition is written for a one or two semester first course in applied statistics and is intended for students who do not have a strong background in mathematics. The only prerequisite is knowledge of elementary algebra. Introductory Statistics, 8th Edition is known for its realistic examples and exercises, clarity and brevity of presentation, and soundness of pedagogical approach. Case studies appear in almost all chapters to provide additional illustrations of the applications of statistics in research and statistical analysis and the text contains a wealth of examples that cover a wide variety of relevant statistical topics.
Author: Douglas C. Montgomery Publisher: John Wiley & Sons ISBN: 1118548507 Category : Mathematics Languages : en Pages : 112
Book Description
As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.
Author: John Verzani Publisher: CRC Press ISBN: 1315360306 Category : Computers Languages : en Pages : 522
Book Description
The 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: Robin H. Lock Publisher: John Wiley & Sons ISBN: 1119308917 Category : Mathematics Languages : en Pages : 290
Book Description
This is the Student Solutions Manual to Accompany Statistics: Unlocking the Power of Data, 2nd Edition. Statistics, 2nd Edition moves the curriculum in innovative ways while still looking relatively familiar. Statistics, 2e utilizes intuitive methods to introduce the fundamental idea of statistical inference. These intuitive methods are enabled through statistical software and are accessible at very early stages of a course. The text also includes the more traditional methods such as t-tests, chi-square tests, etc., but only after students have developed a strong intuitive understanding of inference through randomization methods. The text is designed for use in a one-semester introductory statistics course. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The text is driven by real data and real applications. Students completing the course should be able to accurately interpret statistical results and to analyze straightforward data sets.
Author: Stuart A. Klugman Publisher: John Wiley & Sons ISBN: 1119538033 Category : Business & Economics Languages : en Pages : 218
Book Description
Solutions manual to accompany a text with comprehensive coverage of actuarial modeling techniques The Student Solutions Manual to Accompany Loss Models: From Data to Decisions covers solutions related to the companion text. The manual and text are designed for use by actuaries and those studying for the profession. Readers can learn modeling techniques used across actuarial science. Knowledge of the techniques is also beneficial for those who use loss data to build models for risk assessment.
Author: Neil A. Weiss
Author: Neil A. Weiss
Author: Stephen Kokoska
Author: Sheldon M. Ross
Author: Neil A. Weiss
Author: Prem S. Mann
Author: William B. Craine
Author: Douglas C. Montgomery
Author: John Verzani
Author: Robin H. Lock
Author: Stuart A. Klugman