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Author: M. D. Edge Publisher: ISBN: 0198827628 Category : Mathematics Languages : en Pages : 318
Book Description
Focuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.
Author: M. D. Edge Publisher: ISBN: 0198827628 Category : Mathematics Languages : en Pages : 318
Book Description
Focuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.
Author: Alex Reinhart Publisher: No Starch Press ISBN: 1593276206 Category : Mathematics Languages : en Pages : 177
Book Description
Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.
Author: Mario F. Triola Publisher: Addison-Wesley Longman ISBN: 9780321500243 Category : Mathematical statistics Languages : en Pages : 0
Book Description
Normal 0 false false false Mario Triola's Elementary Statistics remains the market-leading introductory statistics textbook because it engages readers with an abundance of real data in the examples, applications, and exercises. Statistics is all around us in our daily lives, and Triola is dedicated to finding new real-world examples and data sets that make sense for today's reader. The Eleventh Edition contains more than 2000 exercises, 87% of which are new, and 82% of which use real data. It also contains hundreds of examples, 86% of which are new and 94% of which use real data. By analyzing real data, students are able to connect abstract concepts to the world at large. As a result, they gain conceptual understanding and learn to think statistically, using the same methods that professional statisticians employ. Introduction to Statistics; Summarizing and Graphing Data; Statistics for Describing, Exploring, and Comparing Data; Probability; Discrete Probability Distributions; Normal Probability Distributions; Estimates and Sample Sizes; Hypothesis Testing; Inferences from Two Samples; Correlation and Regression; Goodness-of-Fit and Contingency Tables; Analysis of Variance; Nonparametric Statistics; Statistics Process Control; Projects, Procedures, Perspectives For all readers interested in introductory statistics.
Author: Mario F. Triola Publisher: ISBN: 9780201859218 Category : Languages : en Pages : 0
Book Description
Addison-Wesley is proud to celebrate the Tenth Edition of Elementary Statistics.& This text is highly regarded because of its engaging and understandable introduction to statistics. The&author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.
Author: Ron Larson Publisher: Prentice Hall ISBN: 9780131483163 Category : Mathematics Languages : en Pages : 615
Book Description
For algebra-based Introductory Statistics courses. Offering an approach with a visual/graphical emphasis, this text offers a number of examples on the premise that students learn best by doing. This book features an emphasis on interpretation of results and critical thinking over calculations.
Author: Rachel L. Webb Publisher: ISBN: 9781716398919 Category : Languages : en Pages : 458
Book Description
This text is for an introductory level probability and statistics course with an intermediate algebra prerequisite. The focus of the text follows the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (GAISE). Software examples provided for Microsoft Excel, TI-84 & TI-89 calculators. A formula packet and pdf version of the text are available on the website http: //mostlyharmlessstatistics.com. Students new to probability and statistics are sure to benefit from this fully ADA accessible and relevant textbook. The examples resonate with everyday life, the text is approachable, and has a conversational tone to provide an inclusive and easy to read format for students.
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: M. D. Edge
Author: M. D. Edge
Author: Alex Reinhart
Author: William Cyrus Navidi
Author: Mario F. Triola
Author: Mario F. Triola
Author: Ron Larson
Author: Rachel L. Webb
Author: Gareth James
Author: Robert Johnson
Author: BLUMAN