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Author: John J. Kinney Publisher: John Wiley & Sons ISBN: 9780470486962 Category : Mathematics Languages : en Pages : 280
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: John J. Kinney Publisher: John Wiley & Sons ISBN: 9780470486962 Category : Mathematics Languages : en Pages : 280
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
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
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: Christopher Hay-Jahans Publisher: CRC Press ISBN: 042982727X Category : Mathematics Languages : en Pages : 377
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
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: David L. Eldredge Publisher: South Western Educational Publishing ISBN: 9780538890885 Category : Business Languages : en Pages : 0
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: Filomena Pereira-Maxwell Publisher: CRC Press ISBN: 1351643584 Category : Medical Languages : en Pages : 668
Book Description
This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of statistics and research methodology, this text provides clear and succinct explanations, clarifying meaning and showing the interdependencies between important concepts. This edition includes enhanced explanations of statistical concepts and methods—including more illustrative content—for greater accessibility. The book makes frequent use of examples from the medical literature, with reference to landmark studies, ensuring clinical relevance. It remains an ideal aid to accompany the reading and critical appraisal of medical and health care literature, now widely recognized to be a practical lifelong skill required by all health professionals throughout undergraduate and postgraduate studies and during clinical practice.
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: John J. Kinney
Author: John J. Kinney
Author: Roxy Peck
Author: Alejandro A Lazarte
Author: Adam Littig
Author: Christopher Hay-Jahans
Author: Chelsea Myers
Author: David L. Eldredge
Author: Filomena Pereira-Maxwell
Author: Gareth James
Author: Danney Rasco