Susan Rovezzi Carroll, David J. Carroll

How to Become Data Literate (eBook, ePUB)

The Basics for Educators

• Format: ePub

Produktbeschreibung

In this follow up to Statistics Made Simple for School Leaders Carroll and Carroll have provided an updated, easy to comprehend, manual for practitioners. 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 regression 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. 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.

Produktdetails

• Verlag: Bloomsbury eBooks US
• Seitenzahl: 150
• Erscheinungstermin: 16. März 2015
• Englisch
• ISBN-13: 9781475813333
• Artikelnr.: 42720515

Autorenporträt

Susan Rovezzi Carroll, PhD has provided hundreds of graduate students with advice and support on research methods and statistical procedures. She is president of Words & Numbers Research, Inc. which she founded in 1984. David Carroll, MSW is vice president of Words & Numbers Research, Inc. He has several research publications and books to his credit and has expertise in demographic data analysis and the development of performance indicators for assessing outcomes.

Inhaltsangabe

Introduction: The compelling case for data literacy
Chapter One: Speaking the language correctly
Chapter Two: Creating a snap shot of data with a picture
Chapter Three: Presenting a mountain of data with one number
Chapter Four: Understanding why range in your data is important
Chapter Five: Drawing a sample to represent a whole group
Chapter Six: Putting your assumptions to the test
Chapter Seven: T-tests: Examining differences between two groups
Chapter Eight: ANOVA: What if there are more than two groups?
Chapter Nine: Chi Square: Examining distributions for differences
Chapter Ten: Correlations: Detecting relationships
Chapter Eleven: Reporting your data clearly and strategically