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Author: John E. Freund Publisher: Pearson Educación ISBN: 9789701703892 Category : Mathematics Languages : en Pages : 644
Book Description
For a two-semester or a three-quarter calculus-based Introduction to the Mathematics of Statistics course. This classic, calculus-based introduction to the theory - and application - of statistics provides an unusually comprehensive depth and breadth of coverage and reflects the state-of-the-art in statistical thinking, the teaching of statistics, and current practices - including the use of the computer. *NEW - Places greater emphasis on the use of computers in performing statistical calculations. *NEW - Includes new exercises - many of which require the use of a computer. *NEW - Expands coverage of Analysis of Variance to include the two-way analysis-of-variance model with interaction and a discussion of multiple comparisons. *NEW - Adds appendices which summarize the properties of the special probability distributions and density functions that appear in the text. *Places greater emphasis on the use of computers in performing statistical calculations. *Comprehensive coverage of statistical theories. *Features more than 1,100 problems and exercises - divided into theory and applications.
Author: John E. Freund Publisher: Pearson Educación ISBN: 9789701703892 Category : Mathematics Languages : en Pages : 644
Book Description
For a two-semester or a three-quarter calculus-based Introduction to the Mathematics of Statistics course. This classic, calculus-based introduction to the theory - and application - of statistics provides an unusually comprehensive depth and breadth of coverage and reflects the state-of-the-art in statistical thinking, the teaching of statistics, and current practices - including the use of the computer. *NEW - Places greater emphasis on the use of computers in performing statistical calculations. *NEW - Includes new exercises - many of which require the use of a computer. *NEW - Expands coverage of Analysis of Variance to include the two-way analysis-of-variance model with interaction and a discussion of multiple comparisons. *NEW - Adds appendices which summarize the properties of the special probability distributions and density functions that appear in the text. *Places greater emphasis on the use of computers in performing statistical calculations. *Comprehensive coverage of statistical theories. *Features more than 1,100 problems and exercises - divided into theory and applications.
Author: Neil J. Salkind Publisher: Pearson Educación ISBN: 9789701702345 Category : Education Languages : en Pages : 406
Book Description
Book's content and also references for related works of fiction, and other material of a more informal nature. For Psychologists, Management and Businesspersons or other social or behavioral science-related professionals who are looking to sharpen their understanding of research methods.
Author: María Isabel Fernández Aranda Publisher: Lulu.com ISBN: 1291408967 Category : Science Languages : en Pages : 86
Book Description
Iniciamos este libro con algunos conceptos básicos y elementales para una comprensión real e intuitiva de lo que es la Estadística Aplicada, sobre todo su aplicación a los problemas de la Enfermería y especialmente la especialidad de Matrona.
Author: Gareth James Publisher: Springer Nature ISBN: 3031387473 Category : Mathematics Languages : en Pages : 617
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: Barbara Illowsky Publisher: ISBN: Category : Mathematics Languages : en Pages : 2106
Book Description
Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
Author: Christian Heumann Publisher: Springer ISBN: 9783031118326 Category : Mathematics Languages : en Pages : 0
Book Description
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Author: John E. Freund
Author: John E. Freund
Author: Neil J. Salkind
Author: I. Paenson
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Author: María Isabel Fernández Aranda
Author: Gareth James
Author: Barbara Illowsky
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Author: 
Author: Christian Heumann