Learn data
Data LiteracyData 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
Property and Housing Data
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
Meta Research
Nearly 500 reports across a range of topics, catalogued in one central location and mapped out on a visual data tool
Kids and Families Data
Detailed data and general trends displayed through interactive visualizations that make them easy to understand
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.
Learning How To Use GIS
This set of tutorials on Geographic Information Systems (GIS) can be used as part of a structured class or as a stand-alone course. It provides a basic introduction into what a Geographic Information System is and what GIS can be used for. It also features several GIS professionals in different fields and provides suggestions on next steps for students interested in advancing their GIS skills.
About Co.Lab Connect
Co.act Detroit has partnered with nonprofits and business professionals from Southeast Michigan to offer free virtual consultation appointments with subject matter experts in a variety of fields.
These 45-minute sessions provide the opportunity to approach challenges from a fresh perspective and tap into solution-oriented thinking skills.
Data Driven Detroit team members provide our expertise on a variety of data topics during the 3:00 pm sessions each Tuesday.
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