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Statistics Through an Equity Lens [Revised Edition] Yvonne Anthony

Contributor(s): Material type: TextTextSeries: Open textbook libraryDistributor: Minneapolis, MN Open Textbook LibraryPublisher: Boston, MA ROTEL 2024Copyright date: ©2023Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
Subject(s): LOC classification:
  • QA1
  • QA273-280
Online resources:
Contents:
Introduction -- Chapter 1 - An Overview of Statistics -- Chapter 2 - Descriptive Statistics -- Chapter 3 - Probability -- Chapter 4 - Inferential Statistics: Sampling Methods -- Chapter 5 - Significance of Statistical Inference Methods -- Chapter 6 - Correlation and Regression Analysis -- Chapter 7 - Case Studies
Subject: This Open Educational Resource (OER) carries a significant responsibility by presenting statistics through an equity lens. The metaphor of a lens is used intentionally–as the glasses one wears can have a profound effect on what one sees. The book encourages further inspection of the ways in which data is collected, interpreted, and analyzed on a variety of social justice issues, such as health disparities, hunger and food insecurity, homelessness, behavioral health (mental health and substance use), and incarceration of males of color. It also attempts to reveal how the misuse of data can reinforce inequities, for example, by stigmatizing people and labeling neighborhoods as high poverty, violent, and having poor educational opportunities. Whether an intended or unintended consequence, irresponsible data use can contribute to racist impressions of people and communities.
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Introduction -- Chapter 1 - An Overview of Statistics -- Chapter 2 - Descriptive Statistics -- Chapter 3 - Probability -- Chapter 4 - Inferential Statistics: Sampling Methods -- Chapter 5 - Significance of Statistical Inference Methods -- Chapter 6 - Correlation and Regression Analysis -- Chapter 7 - Case Studies

This Open Educational Resource (OER) carries a significant responsibility by presenting statistics through an equity lens. The metaphor of a lens is used intentionally–as the glasses one wears can have a profound effect on what one sees. The book encourages further inspection of the ways in which data is collected, interpreted, and analyzed on a variety of social justice issues, such as health disparities, hunger and food insecurity, homelessness, behavioral health (mental health and substance use), and incarceration of males of color. It also attempts to reveal how the misuse of data can reinforce inequities, for example, by stigmatizing people and labeling neighborhoods as high poverty, violent, and having poor educational opportunities. Whether an intended or unintended consequence, irresponsible data use can contribute to racist impressions of people and communities.

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In English.

Description based on print resource

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