Online Statistics Education PDF Download

Author: David M Lane
Publisher:
ISBN: 9781687894250
Category :
Languages : en
Pages : 406

View

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: H. J. Anderson
Publisher: Trafford Publishing
ISBN: 1412234700
Category : Sports & Recreation
Languages : en
Pages : 188

View

Book Description
Everything you wanted to know about the Canada Cup, the predecessor of the World Cup of Hockey. The Canada Cup saw the birth of international hockey involving NHL players. Following the Summit Series in 1972 and 1974, the world would finally see the nations of Canada, Czechoslovakia, Finland, the Soviet Union, Sweden, the United States and West Germany compete with all their best players for the first time. The Canada Cup gave us some of the greatest games and never-to-be-forgotten moments in hockey history. For more information, please visit the author's website at: www.canadacupofhockey.com

Author: Eugene Demidenko
Publisher: John Wiley & Sons
ISBN: 1118387988
Category : Mathematics
Languages : en
Pages : 880

View

Book Description
Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.

Author: David Spiegelhalter
Publisher: Basic Books
ISBN: 1541618521
Category : Mathematics
Languages : en
Pages : 359

View

Book Description
In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

Author: H.J. Anderson
Publisher: Trafford Publishing
ISBN: 1412055121
Category : History
Languages : en
Pages : 188

View

Book Description
The Canada Cup gave us some the greatest games and never to be forgotten moments in hockey history. Re-live some of those moments with this fascinating insight into the tournament.

Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617

View

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: Openstax
Publisher:
ISBN: 9788565775120
Category : Mathematics
Languages : en
Pages : 914

View

Book Description
Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs. Senior Contributing Authors Barbara Illowsky, De Anza College Susan Dean, De Anza College Contributing Authors Daniel Birmajer, Nazareth College Bryan Blount, Kentucky Wesleyan College Sheri Boyd, Rollins College Matthew Einsohn, Prescott College James Helmreich, Marist College Lynette Kenyon, Collin County Community College Sheldon Lee, Viterbo University Jeff Taub, Maine Maritime Academy

Author: Amar'e Stoudemire
Publisher: Scholastic Inc.
ISBN: 0545473993
Category : Juvenile Fiction
Languages : en
Pages : 115

View

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: Bill James
Publisher:
ISBN:
Category : Baseball
Languages : en
Pages : 618

View

Book Description

Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446

View

Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.