A Probability and Statistics Companion PDF Download

Author: John J. Kinney
Publisher: John Wiley & Sons
ISBN: 9780470486962
Category : Mathematics
Languages : en
Pages : 280

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Book Description
An accessible and engaging introduction to the study of probability and statistics Utilizing entertaining real-world examples, A Probability and Statistics Companion provides aunique, interesting, and accessible introduction to probability and statistics. This one-of-a-kind book delves into practical topics that are crucial in the analysis of sample surveys and experimentation. This handy book contains introductory explanations of the major topics in probability and statistics, including hypothesis testing and regression, while also delving into more advanced topics such as the analysis of sample surveys, analysis of experimental data, and statistical process control. The book recognizes that there are many sampling techniques that can actually improve on simple random sampling, and in addition, an introduction to the design of experiments is provided to reflect recent advances in conducting scientific experiments. This blend of coverage results in the development of a deeper understanding and solid foundation for the study of probability and statistics. Additional topical coverage includes: Probability and sample spaces Choosing the best candidate Acceptance sampling Conditional probability Random variables and discrete probability distributions Waiting time problems Continuous probability distributions Statistical inference Nonparametric methods Least squares and medians Recursions and probability Each chapter contains exercises and explorations for readers who wish to conduct independent projects or investigations. The discussion of most methods is complemented with applications to engaging, real-world scenarios such as winning speeds at the Indianapolis 500 and predicting winners of the World Series. In addition, the book enhances the visual nature of the subject with numerous multidimensional graphical representations of the presented examples. A Probability and Statistics Companion is an excellent book for introductory probability and statistics courses at the undergraduate level. It is also a valuable reference for professionals who use statistical concepts to make informed decisions in their day-to-day work.

Author: Roxy Peck
Publisher: Cengage Learning
ISBN: 9781337705592
Category : Mathematics
Languages : en
Pages : 368

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Book Description
Roxy Peck and Tom Short's STATISTICS COMPANION supports your success in Statistics by providing a review of the necessary Statistics-specific mathematics, study skills, and Statistics-language content. The material you will encounter in the Introductory Statistics course may be new and challenging, but this book and its accompanying resources help build and reinforce the skills you already have--and build upon those skills to help you learn the content of Introductory Statistics. This companion gives you tips for effective studying and a strategy for reading Statistics problems that helps you understand the problem context and interpret results in that context.

Author: Alejandro A Lazarte
Publisher:
ISBN: 9781516599080
Category :
Languages : en
Pages : 252

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Book Description
An Excel Companion for an Introductory Statistics Course in Social and Behavioral Sciences introduces students to the use of Excel to perform basic and intermediate data analyses that are common in the social and behavioral sciences. The companion focuses on using Excel to perform the types of analyses covered in most textbooks within the discipline. The book covers computations of descriptive statistics, hypothesis testing for means up to one-way ANOVA, correlation, and simple linear regression. Students learn how to perform summation in Excel, build pivot tables, and create compelling and accurate distribution graphs. Measures of central tendency, variability, and location are covered. Additional chapters explore normal distribution, random numbers, probability distributions, cross tabulations, and more. All Excel computations described in the companion rely on basic Excel functions and the Data Analysis ToolPak add-on that comes with Excel. Highly practical and accessible, An Excel Companion for an Introductory Statistics Course in Social and Behavioral Sciences is an ideal supplementary text for introductory statistics courses.

Author: Adam Littig
Publisher:
ISBN: 9781543244342
Category :
Languages : en
Pages : 208

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Book Description
Buy a copy at your college bookstore (not here)!

Author: Christopher Hay-Jahans
Publisher: CRC Press
ISBN: 042982727X
Category : Mathematics
Languages : en
Pages : 377

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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: Chelsea Myers
Publisher: Chapman & Hall/CRC
ISBN: 9780429292002
Category : Mathematics
Languages : en
Pages : 169

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Book Description
Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects, which could serve as alternatives to traditional discrete homework problems, will illustrate how to "put the pieces together" and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class. Key features of the text: Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics, regression, two-way tables, hypothesis testing for means and proportions, etc.) so instructors can easily pair this supplementary material with course plans Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework Features real-world datasets from scientific publications in the fields of history, pop culture, business, medicine, and forensics for students to analyze Allows students to gain experience working through a variety of statistical analyses from start to finish The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics. Author After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison, Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath.com.

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: David L. Eldredge
Publisher: South Western Educational Publishing
ISBN: 9780538890885
Category : Business
Languages : en
Pages : 0

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Book Description
Using a familiar tool, such as Excel, enhances the business professionals ability to make better business decisions leading to future success. This manual provides step-by-step instructions for using Excel to solve most of the problems for business statistics. It presents many visual examples of computer screen captures. These show data input, pull-down menus, dialog boxes and statistical results.

Author: J. S. Marron
Publisher: CRC Press
ISBN: 1351189662
Category : Computers
Languages : en
Pages : 436

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Book Description
Object Oriented Data Analysis is a framework that facilitates inter-disciplinary research through new terminology for discussing the often many possible approaches to the analysis of complex data. Such data are naturally arising in a wide variety of areas. This book aims to provide ways of thinking that enable the making of sensible choices. The main points are illustrated with many real data examples, based on the authors' personal experiences, which have motivated the invention of a wide array of analytic methods. While the mathematics go far beyond the usual in statistics (including differential geometry and even topology), the book is aimed at accessibility by graduate students. There is deliberate focus on ideas over mathematical formulas. J. S. Marron is the Amos Hawley Distinguished Professor of Statistics, Professor of Biostatistics, Adjunct Professor of Computer Science, Faculty Member of the Bioinformatics and Computational Biology Curriculum and Research Member of the Lineberger Cancer Center and the Computational Medicine Program, at the University of North Carolina, Chapel Hill. Ian L. Dryden is a Professor in the Department of Mathematics and Statistics at Florida International University in Miami, has served as Head of School of Mathematical Sciences at the University of Nottingham, and is joint author of the acclaimed book Statistical Shape Analysis.

Author: Jessica M. Utts
Publisher: Brooks/Cole
ISBN:
Category : Statistics
Languages : en
Pages : 778

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Book Description
Student CD-ROM contains lab manuals, applets, data sets, presentation slides, Web resources, and tutorial quiz; Interactive video skillbuilder CD-ROM contains video instruction on key examples from the text.