Data Science in Education Using R

Ryan A. Estrellado

ISBN 10: 0367422247 / ISBN 13: 9780367422240

Published by Taylor & Francis Ltd Okt 2020, 2020

About this Item

Neuware.

Seller Inventory # 9780367422240

Bibliographic Details

• Title: Data Science in Education Using R
• Publisher: Taylor & Francis Ltd Okt 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 0367422247
• ISBN 13: 9780367422240
• Binding: Buch
• Condition: Neu
• Dimensions: 246W x 174H x 0D millimeters 246 millimeters width by 174 millimeters height by 0 millimeters depth
• Weight: 720 grams

About this title

Synopsis

Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like?

If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job.

This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.

About the Author

Ryan A. Estrellado has served public schools for over seventeen years as a school psychologist and administrator. Ryan writes about working with data, education and other projects at https://ryanestrellado.com.

Emily A. Freer is the Director of Educational Development and Assessment at the Marquette University School of Dentistry. Learn more about Emily at https://emilyfreer.com.

Jesse Mostipak is the Community Advocate for Kaggle, and has worked both as a high school science teacher and lead data scientist within education non-profits. To follow Jesse’s learning adventures in Python and deep learning, head over to https://jessemaegan.com.

Joshua M. Rosenberg is an Assistant Professor of STEM Education at the University of Tennessee, Knoxville. Follow Josh’s work at http://joshuamrosenberg.com.

Isabella C. Velásquez is a data analyst committed to nonprofit work with the goal of reducing racial and socioeconomic inequities. To follow Isabella’s personal projects, join her at https://ivelasq.rbind.io.