Elementary Applied Statistics PDF Download
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Author: Linton C. Freeman
Publisher: New York : Wiley
ISBN:
Category : Mathematics
Languages : en
Pages : 320
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Book Description
Author: Linton C. Freeman
Publisher: New York : Wiley
ISBN:
Category : Mathematics
Languages : en
Pages : 320
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Book Description
Author: Christopher Hay-Jahans
Publisher: CRC Press
ISBN: 042982727X
Category : Mathematics
Languages : en
Pages : 358
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Book Description
The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples. About the Author: Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.
Author: Linton C. Freeman
Publisher: New York : Wiley
ISBN:
Category : Mathematics
Languages : en
Pages : 320
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Book Description
Author: Marvin Lentner
Publisher:
ISBN: 9780800500221
Category : Statistics
Languages : en
Pages : 428
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Book Description
Author: Linton C. Freeman
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 298
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Book Description
Author: Jack Levin
Publisher: Allyn & Bacon
ISBN: 9780205375790
Category : Social sciences
Languages : en
Pages : 0
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Book Description
A shorter, simplified, paperback, and less expensive version of Levin and Fox's popular introduction to statistics in the social sciences.
Author: William Henry Foddy
Publisher:
ISBN: 9780063121010
Category : Social sciences
Languages : en
Pages : 238
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Book Description
Author: Peter Martin
Publisher: UNSW Press
ISBN: 9780730013877
Category : Statistics
Languages : en
Pages : 186
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Book Description
Produced for units EME489 and EME608 Reasoning and data offered by the Faculty of Education in Deakin University's Open Campus Program.
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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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: William Cyrus Navidi
Publisher:
ISBN: 9780077440619
Category : Mathematical statistics
Languages : en
Pages :
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Book Description
