Activity-Based Statistics
Activity-Based Statistics

Author: Richard L. Scheaffer

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 249

ISBN-13: 1475738439

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This book presents a collection of hands-on activities for students taking introductory statistics, and is designed to engage the student as a participant in the learning process. Intended as a lab manual and organized around the major topics covered in most introductory courses, this book contains more activities than can possibly be covered in one course, allowing flexibility for individual course requirements. Packaged in an inexpensive paperback format, the pages are perforated and 3-hole punched for easy removal of individual activities. The 50+ experiments, models, and simulations included in this book are explained succinctly, giving students a clear description of the activities without extra reading. Many activities are compatible with technology.

Activity-Based Statistics, 2nd Edition Student Guide
Activity-Based Statistics, 2nd Edition Student Guide

Author: Richard L. Scheaffer

Publisher: Wiley

Published: 2008-06-16

Total Pages: 0

ISBN-13: 9780470412091

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Activity-Based Statistics helps build real statistical understanding through a set of innovative hands-on activities that can be used each day in conjunction with other texts. The second edition continues to emphasize discovery by motivating readers to apply the skills they have learned to discover the everyday relevance of statistics. There are over 45 activities and five long-term projects that have been updated and extended to encourage readers to experience statistics in context. While the second edition includes updated technology extensions for Fathom, technology is used throughout the book to extend activities and is not required to complete them.

Teaching Statistics
Teaching Statistics

Author: Andrew Gelman

Publisher: OUP Oxford

Published: 2002-08-08

Total Pages: 353

ISBN-13: 0191606995

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Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.

Statistics for Kids
Statistics for Kids

Author: Scott A. Chamberlin

Publisher: Routledge

Published: 2013

Total Pages: 0

ISBN-13: 9781618210227

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Perhaps the most useful and neglected content area of mathematics is statistics, especially for students in Grades 4-6. Couple that fact with the notion that mathematical modeling is an increasing emphasis in many standards, such as the Common Core State Standards for Mathematics and the NCTM standards, and the necessity for this topic is overdue. In this book, teachers will facilitate learning using model-eliciting activities (MEAs), problem-solving tasks created by mathematics educators to encourage students to investigate concepts in mathematics through the creation of mathematical models. Students will explore statistical concepts including trends, spread of data, standard deviation, variability, correlation, sampling, and more--all of which are designed around topics of interest to students. Grades 4-6

Statistics is Easy
Statistics is Easy

Author: Manpreet Singh Katari

Publisher: Morgan & Claypool Publishers

Published: 2021-04-08

Total Pages: 76

ISBN-13: 1636390900

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Computational analysis of natural science experiments often confronts noisy data due to natural variability in environment or measurement. Drawing conclusions in the face of such noise entails a statistical analysis. Parametric statistical methods assume that the data is a sample from a population that can be characterized by a specific distribution (e.g., a normal distribution). When the assumption is true, parametric approaches can lead to high confidence predictions. However, in many cases particular distribution assumptions do not hold. In that case, assuming a distribution may yield false conclusions. The companion book Statistics is Easy! gave a (nearly) equation-free introduction to nonparametric (i.e., no distribution assumption) statistical methods. The present book applies data preparation, machine learning, and nonparametric statistics to three quite different life science datasets. We provide the code as applied to each dataset in both R and Python 3. We also include exercises for self-study or classroom use.

Activities for Teaching Statistics and Research Methods
Activities for Teaching Statistics and Research Methods

Author: Jeffrey R. Stowell

Publisher: American Psychological Association (APA)

Published: 2017

Total Pages: 0

ISBN-13: 9781433827143

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This book offers original, classroom-tested activities to teach high school and undergraduate students essential concepts in research methods and statistics.

All of Statistics
All of Statistics

Author: Larry Wasserman

Publisher: Springer Science & Business Media

Published: 2013-12-11

Total Pages: 446

ISBN-13: 0387217363

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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.

Activity-Based Intelligence: Principles and Applications
Activity-Based Intelligence: Principles and Applications

Author: Patrick Biltgen

Publisher: Artech House

Published: 2016-01-01

Total Pages: 481

ISBN-13: 1608078779

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This new resource presents the principles and applications in the emerging discipline of Activity-Based Intelligence (ABI). This book will define, clarify, and demystify the tradecraft of ABI by providing concise definitions, clear examples, and thoughtful discussion. Concepts, methods, technologies, and applications of ABI have been developed by and for the intelligence community and in this book you will gain an understanding of ABI principles and be able to apply them to activity based intelligence analysis. The book is intended for intelligence professionals, researchers, intelligence studies, policy makers, government staffers, and industry representatives. This book will help practicing professionals understand ABI and how it can be applied to real-world problems.

Statistics
Statistics

Author: Robin H. Lock

Publisher: John Wiley & Sons

Published: 2020-10-13

Total Pages: 866

ISBN-13: 1119682169

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Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.