Learn data

Data Literacy

Data can be intimidating. We’ve compiled some hands-on experiences and quick reference sheets to help you understand the basics of data and apply them to real-world situations.

Using data can be both integral to your work and help you take it to the next level. On this page, we collect resources that we’ve created to help you gain experience using data that directly relates to your work, including workshop recordings, links to blog posts and tool tutorials, and ways to connect with data experts that you can reach out to for additional coaching in the future. With the resources we’ve created, you can learn how to use our online data tools and visualization resources, as well as strategies for telling compelling stories using data.

Data Analysis Basics

Through blog posts, videos, and other tools we’ve produced a collection of resources that cover some of the key concepts of using and interpreting data.

What is Data?

Data helps to provide insight into our world: as it existed in the past, exists now, and how it might be shaped in the future.

Per Capita Data

One great way to normalize data within various communities is using per capita data, to help ensure that comparisons of these raw numbers won’t favor highly populated communities or leave out lower populations altogether.

Margin of Error

We use our Housing Information Portal to explain what a margin of error is and how to use it.

Critical Data Methods: Mean vs. Median

Defining mean and median, a quick lesson on how to calculate them, and when it makes sense to use each one.

A Guide to Conscious Data Consumption

When consuming or reporting data, it’s important to keep in mind five things about the numbers: Scope, Geography,Availability, Scale, and Source/Methods

Data Quality

Consider the limitations of the data and what the context surrounding that datapoint represents.

Comparing Data: How to Use Reliability Measures in Real Life

One type of statistics that helps compare data points is reliability measures, such as confidence intervals, margins of error, and standard deviation

Constructing an Index

Construct a single measure that would quantify an indicator across geographies

Data Collection Biases

Any and all data is collected through a process which can have built-in biases, structural inequities, and other confounding factors, all of which impact the resulting data we use to make decisions in the world.

Data University Tutorials and Video Sessions

Data University is a workshop series produced in collaboration with Co.act Detroit to support people who work in nonprofits (and everyone else) and want to learn how to incorporate smart data practices into their work. No advanced statistics required!

Virtual Data University

What Is Data

Why Data Matters

Equitable Data Practices: Accessing Data

Equitable Data Practices: Ethical Data Use

Responsible Data Consumption

Tutorials with D3 Tools

Housing Information Portal screenshot with text title Geographic Area Tool

Property and Housing Data

Detailed property data and general housing trends displayed through interactive visualizations that make them easy to understand

 

Screenshot of the Opportunity Youth network map

Opportunity Youth Data

An interactive report detailing our findings from the Opportunity Youth Research Project, including observations about how data collaboratives work and sample data

 

Screenshot of the Report Detroit tool showing overlapping areas of Detroit that have reports written about them

Meta Research

Nearly 500 reports across a range of topics, catalogued in one central location and mapped out on a visual data tool

 

Screenshot of State of the Detroit Child home page

Kids and Families Data

Detailed data and general trends displayed through interactive visualizations that make them easy to understand

 

Housing Information Portal screenshot with text title Geographic Area Tool

Neighborhood Data

The Neighborhood Change Index combines data from five indices: social advantage, housing stability, crime, business, and protective activities

Data in Use at D3

Once you’re familiar with data concepts and are using data in your work, it can be helpful to learn from the example of others. Collected here are various explanatory series and individual posts that demonstrate some examples of how D3 uses data.

Moms, Place, and Low Birth Weight, Part 1: Detroit

In this first blog of the series we focus on Detroit exclusively, investigating the associations between the rate of low birth weight and the mother’s age at the birth of the child; her educational attainment; her marital status; her race; her ethnicity; the adequacy of the prenatal care she received; and the distribution of LBW infants within the city of Detroit.

Who Are the Centenarians? Part 1: Dying at Age 100 or More

In this first blog post, we look at this group not by studying living centenarians but by studying the characteristics of Michigan residents aged 100 or older who died from 2011-2013.

An Open Data Quick Dive: Placing Metro Detroit’s Job Sprawl in a National Context

In this post, we’ll add our own voice to the conversation, placing job sprawl in Metro Detroit into three broad contexts – rapid transit, older industrial cities, and rapidly-developing regions.

Data Show Where Detroit’s Students Live

Creating an interpolated model showing where Detroit public school students are concentrated.

Moms, Place, and Low Birth Weight, Part 2: Does Place Matter?

The second blog focuses on the same factors for the metro Detroit region, which for the purpose of this blog we define as Wayne County outside of Detroit, Oakland County, and Macomb County (“Metro Region”). We compare the associations found for that region with those found for Detroit as a way of asking, “Does place matter?”

Who Are the Centenarians? Part 2: Dying at Age 100+ vs. Dying at Ages 65-99

In this second part we contrast centenarians’ characteristics with those of Michigan residents who died in 2011-2013 at ages 65-69, 70-79, 80-89, and 90-99.

Temporary Assistance for Needy Families

A national comparative analysis of TANF budgets in each state. We looked specifically into programs and funds that can be used directly for early childhood development.

An Analysis of the 100 Worst US Metropolitan Areas to Live with Spring Allergies

Mapping and comparing a study conducted by the AAFA to determine the 100 worst metropolitan areas to live for spring allergy sufferers

Moms, Place, and Low Birth Weight, Part 3: Place and Race Together

In this third blog post we take the examination of associations between mothers’ demographic characteristics and their children’s birth weight even further by adding another layer to the analysis: the mother’s race.

2020 American Community Survey Data: Margin of Error Analysis

In this blog post we explore how the challenges of collecting Census data during the pandemic also has impacted the American Community Survey. Read to learn what we discovered about margins of error and how we will adapt our presentation of data.

Open Data Quick Dive: Metro Taxes

A look into how the average income tax rates compare across metro areas in the country, as well as numbers related to the Earned Income Tax Credit and the educator expenses deduction. Particular focus will be given to the Metro Detroit area and how it compares to the metro areas surrounding a few Rust Belt cities.

Living & Working: LEHD Employment Statistics

An investigation into employment statistics in Detroit. Using the Census’s OnTheMap tool, we demonstrate job density in Detroit, and the inflow/outflow of work in Detroit and the metropolitan statistical area using Longitudinal Employer-Household Dynamics (LEHD) data.

Learning How To Use Census Data

The Decennial Census and the American Community Survey put out an incredible amount of data that is critical to the work we do at D3, and can be an instrumental data source for your work, as well. We’ve put together a separate resource to help you navigate using data from the 2020 Census.

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