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📒Statistics Through Applications ✍ Daren S. Starnes
📝Statistics Through Applications Book Synopsis : Watch a video introduction here. Statistics Through Applications (STA) is the only text written specifically for high school statistics course. Designed to be read, the book takes a data analysis approach that emphasizes conceptual understanding over computation, while recognizing that some computation is necessary. The focus is on the statistical thinking behind data gathering and interpretation. The high school statistics course is often the first applied math course students take. STA engages students in learning how statisticians contribute to our understanding of the world and helps students to become more discerning consumers of the statistics they encounter in ads, economic reports, political campaigns, and elsewhere. New and improved! STA 2e features expanded coverage of probability, a reorganized presentation of data analysis, a new color design and much more. Please see the posted sample chapter or request a copy today to see for yourself.
📒Statistics Through Applications ✍ Daren S. Starnes
📝Statistics Through Applications Book Synopsis : Statistics Through Applications (STA) is the only text written specifically for high school statistics course. Designed to be read, the book takes a data analysis approach that emphasizes conceptual understanding over computation, while recognizing that some computation is necessary. The focus is on the statistical thinking behind data gathering and interpretation. The high school statistics course is often the first applied math course students take. STA engages students in learning how statisticians contribute to our understanding of the world and helps students to become more discerning consumers of the statistics they encounter in ads, economic reports, political campaigns, and elsewhere. New and improved! STA 2e features expanded coverage of probability, a reorganized presentation of data analysis, a new color design and much more.
📒Statistics Through Applications ✍ Dan Yates
📝Statistics Through Applications Book Synopsis : The NCTM urges the study of statistics in high school, and many schools have designed courses based on these NCTM recommendations. Now from the authors of the overwhelming favorite for the AP Statistics course (The Practice of Statistics) comes the first text written exclusively for a non-AP level high introduction to statistics for high school students. Statistics Through Applications is the ideal alternative for juniors and seniors not going into high level courses such as calculus, but who are interested in an introduction to the important topics of statistics. The book's data analysis approach moves students away from monotonous computation to focus on the statistical thinking behind data gathering and interpretation. This approach more accurately reflects the way working statisticians contribute to our understanding of the world. It also helps students be more discerning consumers of statistics, teaching them to look closely at what the numbers from surveys, election polls, and medical studies are really saying. State Correlationshttp://www.bfwpub.com/pdfs/yatessta/state.htm
📒Stat Labs ✍ Deborah Nolan
📝Stat Labs Book Synopsis : 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.
📒Spatial Statistics Through Applications ✍ Jorge Mateu
📝Spatial Statistics Through Applications Book Synopsis : This volume provides an overview of existing methodology, together with details of new theoretical developments and some practical applications.
📝Solutions Manual for Statistics Through Applications Book Synopsis : Instructors Solutions Manual t./a main text ISBN 0716747723
📝Teacher s Resource Binder for Statistics Through Applications Book Synopsis : Teachers Resource Binder to accompany Statistics through Applications. Please see main text ISBN 0716747723 for further details.
📝Foundations and Applications of Statistics An Introduction Using R Second Edition Book Synopsis : Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.
📒An Introduction To Statistical Learning ✍ Gareth James
📝An Introduction to Statistical Learning Book Synopsis : 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 to marketing to 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, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
📒Handbook Of Statistical Analysis And Data Mining Applications ✍ Robert Nisbet
📝Handbook of Statistical Analysis and Data Mining Applications Book Synopsis : Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications