The classic guide to an unmedicated childbirth, fully revised for the twenty-first century—with updated information and attractive new illustrations and photos throughout. For women birthing vaginally, 90% of Bradley births are drug-free! The Bradley Method®, used and praised by women for almost seventy years, prepares you for drug and surgery-free childbirth and puts you in control by providing the tools to navigate evidence-based care. Certified childbirth educator Susan McCutcheon, one of Dr. Bradley’s first students, now makes this natural approach to childbirth more accessible than ever. You will learn: • Exercises and nutrition to get your body ready for birthing • To defuse fear by understanding all aspects of laboring • How to involve your partner as a birth coach and a fully engaged participant • What’s driving the induction epidemic and how to avoid an unnecessary induction • What’s driving the cesarean surgery epidemic and how to reduce your risk • How to get the information you need to make informed decisions about your birth “The Bradley Method’s simple objective, through relaxation, breathing, and visualization, is a birth free of the interventions frequently offered to women in the different stages of childbirth: fetal monitors, drug-induced labor, anesthesia, episiotomy, and Caesarean section. (Its) other defining feature, the husband’s active participation in the delivery, is critical to this overall goal of an intervention-free birth.”—Mothering
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Provides administrators a blueprint for creating, sustaining, and growing a 3 year bachelors degree program at higher education institutions of all types and sizes.
This practical, easy-to-read guide explains how to raise the rigor for students with special needs so they can achieve higher levels of learning. Learn how to set clear goals and expectations establish a climate of success scaffold and model lessons use graphic organizers and "think-alouds" apply modifications and accommodations use rigorous questioning strategies differentiate instruction increase family involvement Get even more out of this book by discussing it with others! It’s ideal for study groups and the appendix features a detailed guide on how to make it work for your group! Bonus! You get a great variety of handy black line masters for use in your own classroom.
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.
*Newbery Honor Book* *Boston Globe-Horn Book Honor* A nuanced and fierce middle grade novel about sisterhood and sexual abuse, by two-time Newbery Honor winner and #1 New York Times best seller Kimberly Brubaker Bradley, author of The War that Saved My Life "Fighting Words is raw, it is real, it is necessary, a must-read for children and their adults—a total triumph in all ways." —Holly Goldberg Sloan, New York Times bestselling author of Counting by 7s Ten-year-old Della has always had her older sister, Suki: When their mom went to prison, Della had Suki. When their mom's boyfriend took them in, Della had Suki. When that same boyfriend did something so awful they had to run fast, Della had Suki. Suki is Della's own wolf--her protector. But who has been protecting Suki? Della might get told off for swearing at school, but she has always known how to keep quiet where it counts. Then Suki tries to kill herself, and Della's world turns so far upside down, it feels like it's shaking her by the ankles. Maybe she's been quiet about the wrong things. Maybe it's time to be loud. In this powerful novel that explodes the stigma around child sexual abuse and leavens an intense tale with compassion and humor, Kimberly Brubaker Bradley tells a story about two sisters, linked by love and trauma, who must find their own voices before they can find their way back to each other. "Della’s matter-of-fact narration manages to be as funny and charming as it is devastatingly sad. . . . This is a novel about trauma [but] more than that, it’s a book about resilience, strength and healing. For every young reader who decides to wait . . . there will be others for whom this is the exact book they need right now." —New York Times Book Review "One of the most important books ever written for kids."—Colby Sharp of Nerdy Book Club "One for the history books."—Betsy Bird for A Fuse #8 Production/SLJ "Gripping. Life-changing...I am awe-struck."—Donna Gephart, author of Lily and Dunkin "Compassionate, truthful, and beautiful."—Elana K. Arnold, author of Damsel "I am blown away. [This] may be Kimberly Brubaker Bradley's best work yet."—Barbara Dee, author of Maybe He Just Likes You "A book that lets [kids] know they have never been alone. And never will be."—Kat Yeh, author of The Truth About Twinkie Pie "Meets the criteria of great children's literature that [will] resonate with adults too."—Bitch Media * "At once heartbreaking and hopeful."—Kirkus (starred review) * "Honest [and] empowering...An important book for readers of all ages."—SLJ (starred review) * "Sensitive[,] deft, and vivid."—BCCB (starred review) * "Prepare to read furiously."—Booklist (starred review) * "An essential, powerful mirror and window for any reader."—PW (starred review) * "Enlightening, empowering and--yes--uplifting."—BookPage (starred review) * "Unforgettable."—The Horn Book (starred review)
To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field. The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know. The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.