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How to Become Data Literate

The Basics for Educators 2ed
  • ISBN-13: 9781475813326
  • Publisher: ROWMAN & LITTLEFIELD PUBLISHERS
    Imprint: ROWMAN & LITTLEFIELD PUBLISHERS
  • By Susan Rovezzi Carroll, By David J. Carroll
  • Price: AUD $76.99
  • Stock: 0 in stock
  • Availability: This book is temporarily out of stock, order will be despatched as soon as fresh stock is received.
  • Local release date: 14/05/2015
  • Format: Paperback (235.00mm X 145.00mm) 132 pages Weight: 210g
  • Categories: Education [JN]
Description
Table of
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Now more than ever, educators are being held accountable by taxpayers, students, parents, government officials and the business community for supportable documentation of educational results. Data management has become everyone's job and everyone's concern. But the egression of data has exposed a raw nerve. The lack of comfort that many educators have in working with data poses a great challenge as school districts make the transition from a data rich to an information rich environment. How to Become Data Literate is the solution. It is clear that educators need the ability to formulate and answer questions using data as part of evidence-based thinking, selecting and using appropriate data tools, interpreting information from data, evaluating evidence-based differences, using data to solve real problems and communicating solutions. This book is intended to be a user-friendly, educator's primer. It will leave the reader with the confident attitude that "I can do this." In the long run, it is intended to underscore the magnificence of data. Decisions based on excellent data produce meaningful action strategies that benefit students, parents, staff, and the community at large.
Introduction The compelling case for data literacy One Speaking the language correctly Two Creating a snap shot of data with a picture Three Presenting a mountain of data with one number Four Understanding why range in your data is important Five Drawing a sample to represent a whole group Six Putting your assumptions to the test Seven T-tests: Examining differences between two groups Eight ANOVA: What if there are more than two groups? Nine Chi Square: Examining distributions for differences Ten Correlations: Detecting relationships Eleven Reporting your data clearly and strategically
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