1: Reading Science Articles
2: Reading Materials Written for Broader Publics
3: Describing Data
4: Communicating Through Statistical Graphs
5: Communicating through Code
6: Organizing the Story
7: Writing the First Draft
8: Taking Care with Statistical Terms
9: Crafting Words and Sentences
10: Revising: Drafts #2 ThroughEL
11: Embracing Your Role as a Scientist
12: Building a Portfolio
Deborah Nolan is Professor of Statistics and Associate Dean for
Undergraduate Education in the Division of Computing, Data Science,
and Society at the University of California, Berkeley, where she
holds the Zaffaroni Family Chair in Undergraduate Education. Her
research has involved the empirical process, high-dimensional
modeling, and, more recently, technology in education and
reproducible research.
Sara Stoudt is an applied statistician whose work primarily focuses
on environmental and ecological applications. She is currently a
lecturer at Smith College. She received her PhD in Statistics from
UC Berkeley. Prior to that she received a B.A. in Mathematics (with
an emphasis on statistics) from Smith College.
This book about technical writing is particularly suitable (and
necessary) for students in data science, or in any mathematical
science. It begins with chapters on how to read technical articles,
science news stories, and press releases ("examine the argument");
continues with chapters on how to describe and present data and
code; advises how to get started writing ("who is the audience?");
and emphasizes the importance of editing and revising. A concluding
chapter offers 22 imaginative exercises.
*Mathematics Magazine*
excellent presentation.
*T. J. Rao, zb Math Open*
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