R Companion to Elementary Applied Statistics

R Companion to Elementary Applied Statistics PDF

Author: Christopher Hay-Jahans

Publisher: CRC Press

Published: 2019-01-02

Total Pages: 358

ISBN-13: 042982727X

DOWNLOAD EBOOK →

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.

An Introduction to Statistical Learning

An Introduction to Statistical Learning PDF

Author: Gareth James

Publisher: Springer Nature

Published: 2023-08-01

Total Pages: 617

ISBN-13: 3031387473

DOWNLOAD EBOOK →

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.

Elementary Applied Statistics

Elementary Applied Statistics PDF

Author: Peter Martin

Publisher: UNSW Press

Published: 1995

Total Pages: 186

ISBN-13: 9780730013877

DOWNLOAD EBOOK →

Produced for units EME489 and EME608 Reasoning and data offered by the Faculty of Education in Deakin University's Open Campus Program.

Elementary Stochastic Calculus with Finance in View

Elementary Stochastic Calculus with Finance in View PDF

Author: Thomas Mikosch

Publisher: World Scientific

Published: 1998

Total Pages: 230

ISBN-13: 9789810235437

DOWNLOAD EBOOK →

Modelling with the Ito integral or stochastic differential equations has become increasingly important in various applied fields, including physics, biology, chemistry and finance. However, stochastic calculus is based on a deep mathematical theory. This book is suitable for the reader without a deep mathematical background. It gives an elementary introduction to that area of probability theory, without burdening the reader with a great deal of measure theory. Applications are taken from stochastic finance. In particular, the Black -- Scholes option pricing formula is derived. The book can serve as a text for a course on stochastic calculus for non-mathematicians or as elementary reading material for anyone who wants to learn about Ito calculus and/or stochastic finance.

Elementary Statistics

Elementary Statistics PDF

Author: Nancy Pfenning

Publisher: Thomson Brooks/Cole

Published: 2011

Total Pages: 735

ISBN-13: 9780495831587

DOWNLOAD EBOOK →

Using a successfully class-tested approach that gives coherence to a broad range of introductory topics, this innovative text provides students with a big picture view of statistics as well as problem-solving strategies that can be applied to the majority of questions that introductory-statistics students will encounter. Author Nancy Pfenning organizes content around four basic processes of statistics: producing data, displaying and summarizing data, understanding probability, and using probability to perform statistical inference. Within this framework, the book progresses systematically through five basic situations involving values of variables (quantitative, categorical, or a blend). As a result, students learn to identify which situation applies to a specific statistical problem and how to choose the correct display, summary, or inference tool. As students gain proficiency in specific statistical techniques, the author also points out connections among topics and techniques to help them gain a perspective on statistics as a whole. More than 1,000 real-life examples and categorized exercises support the approach, engaging students in practicing and developing a variety of skills.

Lanterna Rally - Theme by Grace Themes