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Author: Amar'e Stoudemire Publisher: Scholastic Inc. ISBN: 0545473993 Category : Juvenile Fiction Languages : en Pages : 115
Book Description
STAT: Standing Tall And Talented-- A slam-dunk new fiction series from NBA superstar Amar'e Stoudemire! Eleven-year-old Amar'e Stoudemire has a lot going on. He loves to go skateboarding in the park. He takes his school work very seriously. He helps out with his dad's landscaping company. And he likes to play basketball with his best friends-but just for fun. When a group of older kids start disrespecting his boys on their neighborhood basketball court, there is only one solution. Amar'e must step in and use his athletic ability and intelligence to save the day. This experience leads Amar'e to realize that basketball is his true passion.Based on the life of All-Star NBA sensation Amar'e Stoudemire, who overcame many obstacles to become one of the most popular figures in sports today. Amar'e is just as versatile in his off the court life as he is on. He is devoted to several charities. He promotes literacy and education. He is a media darling. And he has an amazing story to tell in this heartfelt, accessible middle-grade series.
Author: Amar'e Stoudemire Publisher: Scholastic Inc. ISBN: 0545473993 Category : Juvenile Fiction Languages : en Pages : 115
Book Description
STAT: Standing Tall And Talented-- A slam-dunk new fiction series from NBA superstar Amar'e Stoudemire! Eleven-year-old Amar'e Stoudemire has a lot going on. He loves to go skateboarding in the park. He takes his school work very seriously. He helps out with his dad's landscaping company. And he likes to play basketball with his best friends-but just for fun. When a group of older kids start disrespecting his boys on their neighborhood basketball court, there is only one solution. Amar'e must step in and use his athletic ability and intelligence to save the day. This experience leads Amar'e to realize that basketball is his true passion.Based on the life of All-Star NBA sensation Amar'e Stoudemire, who overcame many obstacles to become one of the most popular figures in sports today. Amar'e is just as versatile in his off the court life as he is on. He is devoted to several charities. He promotes literacy and education. He is a media darling. And he has an amazing story to tell in this heartfelt, accessible middle-grade series.
Author: David M Lane Publisher: ISBN: 9781687894250 Category : Languages : en Pages : 406
Book Description
Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.This print edition of the public domain textbook gives the student an opportunity to own a physical copy to help enhance their educational experience. This part I features the book Front Matter, Chapters 1-10, and the full Glossary. Chapters Include:: I. Introduction, II. Graphing Distributions, III. Summarizing Distributions, IV. Describing Bivariate Data, V. Probability, VI. Research Design, VII. Normal Distributions, VIII. Advanced Graphs, IX. Sampling Distributions, and X. Estimation. Online Statistics Education: A Multimedia Course of Study (http: //onlinestatbook.com/). Project Leader: David M. Lane, Rice University.
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: Deborah Nolan Publisher: Springer Science & Business Media ISBN: 0387227431 Category : Mathematics Languages : en Pages : 292
Book Description
Integrating the theory and practice of statistics through a series of case studies, each lab introduces a problem, provides some scientific background, suggests investigations for the data, and provides a summary of the theory used in each case. Aimed at upper-division students.
Author: Luke Tierney Publisher: John Wiley & Sons ISBN: 0470317566 Category : Mathematics Languages : en Pages : 418
Book Description
Written for the professional statistician or graduate statistics student, the primary objective of this book is to describe a system, based on the LISP language, for statistical computing and dynamic graphics to show how it can be used as an effective platform for a wide range of statistical computing tasks ranging from basic calculations to customizing dynamic graphs. In addition, it introduces object-oriented programming and graphics programming in a statistical context. The discussion of these ideas is based on the Lisp-Stat system; readers with access to such a system can reproduce the examples presented and use them as a basis for further experimentation and study.
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: Joseph K. Blitzstein Publisher: CRC Press ISBN: 1466575573 Category : Mathematics Languages : en Pages : 599
Book Description
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
Author: Andrew Gelman Publisher: CRC Press ISBN: 1439840954 Category : Mathematics Languages : en Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Author: Allen B. Downey Publisher: "O'Reilly Media, Inc." ISBN: 1491907363 Category : Computers Languages : en Pages : 284
Book Description
If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data
Author: Amar'e Stoudemire
Author: Amar'e Stoudemire
Author: David M Lane
Author: Barbara Illowsky
Author: Deborah Nolan
Author: Luke Tierney
Author: Gareth James
Author: Joseph K. Blitzstein
Author: Andrew Gelman
Author: Allen B. Downey
Author: Becky Durfee