Teaching Statistics: A Bag of Tricks

This volume takes a positive spin on the field of statistics. Statistics is seen by students as difficult and boring, however, the authors of this book have eliminated that theory. Teaching Statistics: A Bag Of Tricks, brings together a complete set of examples, demonstrations and projects that not only will increase class participation but will help to eliminate any negative feelings toward the area of statistics.

Business & Money

Gelman, Andrew

Nolan, Deborah

Education & Reference

Oxford University Press

This volume takes a positive spin on the field of statistics. Statistics is seen by students as difficult and boring, however, the authors of this book have eliminated that theory. Teaching Statistics: A Bag Of Tricks, brings together a complete set of examples, demonstrations and projects that not only will increase class participation but will help to eliminate any negative feelings toward the area of statistics.

Science & Math

Mathematics

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, 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, activities, examples, and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'-- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.

Communicating with Data: The Art of Writing for Data Science

Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.

Stoudt, Sara

History & Philosophy

Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how todistill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a coursewith a writing component.Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysispipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way,general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extendthe guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.

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.

Stat Labs: Mathematical Statistics Through Applications (Springer Texts in Statistics)

Biological Sciences

Springer

This collection of intriguing essays describes important applications of statistics and probability in many fields. Instead of teaching methods, the essays illustrate past accomplishments and current uses of statistics and probability. Surveys, questionnaires, experiments, and observational studies are also presented to help the student better understand the importance of the influence of statistics on each topic covered within the separate essays. The overarching goal of STATISTICS: A GUIDE TO THE UNKNOWN is to demonstrate the wide use and importance of statistics through an integrated set of case studies that are readable, interesting, and meaningful to the general public.

Statistics: A Guide to the Unknown

Peck, Roxy

Cobb, George W.

Casella, George

Hoerl, Roger

Duxbury Press

Mary Ellen Carey, an attorney and newly divorced suburban mom of three, finds her quiet, humdrum life suddenly disrupted by David Anderson, her eighteen-year-old client. By representing his minor criminal case, she is dragged into a world of crime and international intrigue. Gerard Fitzgerald, better known as Fitz, is a Newark policeman, the coach of Mary Ellen's son's soccer team, and a man she finds arrogant and paternalistic. Fitz becomes her unlikely protector when she and her children's lives are threatened. From the leafy suburbs of northern New Jersey to the pristine beaches of North Carolina's Outer Banks to the streets and Port of Newark, New Jersey, Mary Ellen and Fitz are pursued by international gangsters who will stop at nothing. But even with death stalking their tracks, Mary Ellen and Fitz's unexpected mutual attraction becomes impossible to ignore.

Conflict of Interest

Literature & Fiction

United States

Montlake Romance

As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. <ul> <li>Refine a question of interest to one that can be studied with data</li> <li>Pursue data collection that may involve text processing, web scraping, etc.</li> <li>Glean valuable insights about data through data cleaning, exploration, and visualization</li> <li>Learn how to use modeling to describe the data</li> <li>Generalize findings beyond the data</li> </ul>

Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python

Computers & Technology

Lau, Sam

Gonzalez, Joseph

Programming Languages

O'Reilly Media

See the best price to sell, buy, or rent books by Nolan, Deborah. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Nolan, Deborah

See the best price to sell, buy, or rent books by Nolan, Deborah. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Teaching Statistics: A Bag of Tricks

Teaching Statistics: A Bag of Tricks

Teaching Statistics: A Bag of Tricks

Teaching Statistics: A Bag of Tricks

Communicating with Data: The Art of Writing for Data Science

Communicating with Data: The Art of Writing for Data Science

Stat Labs: Mathematical Statistics Through Applications (Springer Texts in Statistics)

Statistics: A Guide to the Unknown

Conflict of Interest

Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python