B8 utilize data to advocate keith wiley - hac


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One’s position is only as strong as the information one uses to support it, no matter how worthwhile the endeavor. Making the case for housing assistance in rural America is no different. Understanding and presenting housing data effectively is a key element of advocating for families, seniors, and veterans in need. The ability to access and use data, such as the Census Bureau’s American Community Survey, is a powerful tool. This workshop will help familiarize participants with accessing data and will present ways data can be used to most effectively advocate for rural housing needs.

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  • This is just an intro slide, no need to spend any time with really. I consider this to just be a formality.
  • This slide will just show a picture of the sample website, what it will look like. I simply want to explain here when we expect/hope the website will be up and running. I also want to ask the attendees if they will be willing to beta test the website. This means early access. We would provide them with an information request-Median Income for counties in Alabama, and have them try to execute the search. The idea is to identify any bugs in the system before it goes public.
  • First Bullet: I want to note that the ACS data in the portal contains demographic (age, race, pop counts, etc.), economic(Employment, Income, Poverty, etc.), and housing attributes(Tenure, Structure type, Costs, etc.). The HMDA data describes home loan applications information-again I could give an example (denials, high cost loans, etc.)Second Bullet: The data portal makes available to users the data found in Taking Stock. Just mention here that the data is at the nation, state and county level.
  • First Bullet: Explain that a user will be able to generate a basic search that identifies the most common, fact sheet type, data. We will call it the rural 100. It will include information like (Population, Poverty, Income, Educational Level, etc.)Second Bullet: Explain that, at the nation and state level, the data will be separated out for small town and rural areas making it possible to look specifically at those populations. See HAC website for definition of small town and rural areas.
  • Picture from sample website to show how one can select data. It would be nice if we could show the option for Rural 100 and then how a specific variable search could be completed.
  • Picture from sample website to show output. I like the side by side small town & rural and united states presentation. I want to explain that he data can be extracted in PDF and excel form. Also, make mention of the red, yellow, green reliability measure-see next slide.
  • The above contains an example just to show how the numbers can have a large margin of error. This is just a quick calculation for a very small county in the panhandle of Oklahoma. The idea is that the margins of error, when talking about small, sparsely populated, rural areas, can be quite large and mean that the estimates make not be the most accurate or precise. Big difference when talking about 25 or 82 for such a small population.The index is simply something to make one aware of this issue. It does not say to not use the data. It simply suggest looking at margin of error if you are going to use it.
  • B8 utilize data to advocate keith wiley - hac

    2. 2. DATA CONTENTSData Source  Census 2010 SF1  ACS 2006-10 Five-Year Estimates  Home Mortgage Disclosure Act (HMDA) Data 2010Taking Stock Report Data Available  Nation, State, and County Geography  No High Needs Region Information
    3. 3. DATA SEARCHESTwo Search Levels  Fact Sheet-Rural 100 Variables  Specific Attribute SearchGeography  Small Town & Rural, Suburban & Exurban and Urban Geographic Breakdown – National and State Measures  Single Geography Breakdown -County MeasuresAccess from HAC website
    4. 4. RELIABILITY INDEX Some Estimates have a large margins of error  Issue with sparsely populated rural areas  Cimarron County, Oklahoma (Pop. 2,652) Age Group: Poverty Estimate Upper Bound Lower Bound Number Percent Number Percent Number Percent Under 18 Total 620 Under 18 Living in Poverty 216 34.8 299 48.2 133 21.5 Index attempts to make user aware issue  Dark Green - Very Reliable  Light Green - Generally Reliable  Yellow - Caution (Review Census Margin of Error)  Gray - Not Available or Not Calculated
    5. 5. BEST TESTING DATA PORTAL Review Data Portal Test Search to identify bugs Leave email and will contact