Class prep Go to S:\classes\UEP_ENV Copy whole folder “American Community Survey Error Exploration” to your Desktop Make writable: right-click on folder => properties => uncheck read-only
Feb 24, 2016
Class prep
Go to S:\classes\UEP_ENV Copy whole folder “American Community
Survey Error Exploration” to your Desktop Make writable: right-click on folder =>
properties => uncheck read-only
Class prep
1 Using Windows Explorer, go to the following folder:American Community Survey Error Exploration \AFF_data_tables\ Median_HH_Income_tract
2 Open:a ACS_10_SF4_B19013_metadata.csv – this is the metadata
file for the ACS dataa ACS_10_SF4_B19013_Med_HH_Income.xlsx – this is the
data table (median household income)
Today
Census mapping basics review and questions
Understanding American Community Survey margin of errors
Calculating a reliability index (coefficient of variation or CV)
Visualizing the CV on a map
Questions about joining tables to geography?
Federal Information Processing Standards (FIPS) Codes
Area Name FIPSState Massachusetts 25County Suffolk 25025Tract 000601 25025000601
We JOIN the data table to the geography table using the common ID column
Mapping Numbers
Graduated color
Graduated Colors…number of renters
Graduated Symbols…number of renters
Normalization (“divide by”)
Number of population in rental units normalized by total population in occupied housing units
Fraction of renters living in each tract out of total population in occupied housing units
Using “Normalization”
Normalize by means “divide by” Percentage – e.g., number of renters over
total population in occupied housing Result is a fraction, e.g., .45 Fractions are translated into percentages by
multiplying by 100 .45 = 45%
Density – population normalized by area (e.g., sq mi, acre)
Classes and Classification Methods
Classes and Classification Methods
Classification methods Details from
ArcGIS 10.1 Help – standard classification methods1. Natural breaks – good for skewed data
2. Equal interval, defined interval, and standard deviation – good for evenly distributed data to show differences
3. Quantiles - good for evenly distributed data to show relative difference (e.g., top and bottom 20 percentile
4. Geometric interval – compromise that attempts to have similar number of features in each class with intervals being roughly the same
Classification methods
Details from ArcGIS 10.1 Help – standard classification methods Equal interval Defined interval Natural breaks Quantiles Standard deviation Geometric interval
Try them out!
Which classification methods is best?
Formatting numeric labels
But make it better!
Clutter and data speak! Clearer and cleaner
Review
Categories versus numbers Proportional versus graduated symbols Understanding classification methods
No “right” method – explore Different methods => very different results Number of classes – hard to distinguish over 6
Understanding normalization (“divide by”)
Mapping a particular area – two selection options: Select the town first, then perform select by
location to get all tracts that intersect that town (or have their centroid in that town)
Zoom into an area slightly larger than the region you want to map, then interactively select all the tracts from in that area (e.g., use the select tool to make a box around them)
Then Create Layer from Selected Features
Copying and pasting the same layer in your table of contents If you want to map several variables that are
within the same joined table(s), you can simply copy and paste the layer so that you have another copy
Then create maps from a different variable in each layer
Make sure to change title, legend
American Community Survey
What users need to know
Test: why do we need to use ACS data in policy / environmental analysis?
Because it has important information about our communities…
Because it has important information about our communities…
So we need to learn to use the information reliably…
And especially to understand the margin of error for ACS estimates
Review – What is the ACS?
American Community Survey A continuous monthly survey of households Long set of questions covering many topics Data is released once a year
1 Year averages – areas with a population 65,000+ 3 Year averages – areas with a population 20,000+ 5 Year averages - all other areas (including census
tracts and blockgroups)
E.g., average number of people commuting by bicycle for 2007-2011
Use Census 2010 data where possible because it is 100% survey, thus has smaller sampling error Population Counts
Age Race / Hispanic Ethnicity
Housing Unit Counts and Tenure (rented, owner-occupied)
Household and Family Relationships
ACS: Use the highest aggregation you can in terms of tables (can be hard to find)
ACS and Margin of Error
Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimatesUniverse is workers 16 and over
Workers 16 and Over
Open the Excel files…
a ACS_10_SF4_B19013_Med_HH_Income.xlsx – this is the data table (median household income)
a ACS_10_SF4_B19013_metadata.csv – this is the metadata file for the ACS data
Metadata file and data table…
So let’s understand the margin of error…
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What is Sampling Error?
Definition
The uncertainty associated with an estimate that is based on data gathered from a sample of the population rather than the full population
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Illustration of Sampling ErrorEstimate average number of children per household for a population with 3 households living in a block:
Household A has 1 childHousehold B has 2 childrenHousehold C has 3 children
The block average based on the full population is two children per household: (1+2+3)/3
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Conceptualizing Sampling ErrorThree different samples of 2 households:
1. Households A and B (1 child, 2 children)2. Households B and C (2 children, 3 children)3. Households A and C (1 child, 3 children)
Three different averages based on which sample is used:
4. (1 + 2) / 2 = 1.5 children 5. (2 + 3) / 2 = 2.5 children 6. (1 + 3) / 2 = 2 children
Sampling Error
Census 2010 is a 100% survey so has smaller error
ACS data is based on samples – error is larger
The smaller the geography, the larger the error (because the sample is smaller)
Especially true for variables that sample a small number of people, e.g., bike commuters
ACS and Margin of Error
Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimatesUniverse is workers 16 and over
Workers 16 and Over
American Community Survey and sampling error
The margin of error is calculated and included with each estimate
Calculated at 90% confidence level
What does that mean?
ACS and Margin of Error
Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimatesUniverse is workers 16 and over
Workers 16 and Over
Confidence level of 90% We don’t know for sure how many people in
Tract 3.02 take public transit to work Based on the ACS sample, our estimate over 5
years is that an average of 747 people take transit, +/- 226 at 90% confidence level
If we did many, many samples of that same tract, 90% of the time the resulting range (521-973 people) would contain the real number of commuters taking transit.
10% of the time it would not
Confidence level of 90%
The confidence level of a margin of error indicates the likelihood that the true population value (real number) falls within the margin of error
We can be 90% confident that somewhere between 571 and 973 people take transit to work in tract 3.02
Also we know that Tract 3.02 has somewhere between 1958 and 2684 workers)
So maybe half the workers take transit, or maybe just a fifth of them do. Ugh!!!
If using ACS data, pay attention to margin of error!
ACS table from American Factfinder….
Use metadata file plus AFF web site
This table is showing Educational Attainment for universe of people 25 years and older
Use AFF web site plus metadata file
Bottom line for ACS More up to date information Continuous versus point in time
measurement 5 year estimates are the most reliable
because they have the largest samples But…
Poorer precision at finer scales (e.g., census tract) or areas of low population (rural areas)
Poorer precision for variables with low numbers (e.g., people who bike to work)
Don’t go any lower than tracts for mapping ACS data
Geographic Hierarchy
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Measures associated with sampling error
Look at Excel file for Med_HH_Income
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Measures Associated with Sampling Error Standard Error (SE)
Margin of Error (MOE)
Coefficient of Variation (CV)
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Standard Error (SE) Definition
A measure of the variability of an estimate due to sampling
Depends on variability in the population and sample size
FormulaSE = MOE / 1.645 (for 90% confidence level)
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Margin of Error (MOE) Definition
A measure of the precision of an estimate at a given level of confidence (90%, 95%, 99%)
MOEs at the 90% confidence level are published for all ACS estimates
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Coefficient of Variation (CV)
DefinitionThe relative amount of sampling error associated with a sample estimate
A measure of reliability
FormulaCV = Standard Error / Estimate * 100%
CV% is a measure of reliability. So what is a good CV %? No agreement
Depends on purpose
Census case studies: less than 15% may be reliable 15-30% - not reliable, be very careful Over 30% - not reliable, use with extreme caution
To calculate CV, we first calculate the SE:SE = (MOE / 1.645)
Then the CV% formula is:
CV = (SE / estimate)*100
Two examples
Median household income and biking to work
Why do you think median household income generally show lower CVs (more reliable estimates)?
Exploring Error and the American Community Survey
Your turn!
The American Community Survey Margin of Error Tutorial goes through all this, so do this on your own time for practice
Census data table modifications Preparing data takes understanding and time Probably best to do it in Excel ahead of time Always remember to process the GeoID2
field to make it text To be compatible with shape file:
Column names – 10 characters max, no spaces or symbols
Close Excel tables before opening ArcMap
From desktop, open the following mapfile American Community Survey Error
Exploration \ Exploring Error in the American Community Survey.mxd
Showing in ArcMap Join the fixed Household Median Income
table to Census Tract shape file Create a map of Household Median income –
5 classes by quantiles Right-click and copy tract layer Right-click on Layers and choose Paste
Layers Map CV – 3 classes, with breaks at 15, 30,
and max value
Symbolizing CV with hatch patterns
Hands on exploration of commute data
GIS Tools for Mapping ACS Estimates and Data Quality Informationhttp://gesg.gmu.edu/
For your census mapping assignment You need to make 6 maps 6 different census variables (not necessarily
from 6 different tables) At least two of the maps have to show ACS
variables You don’t have to show CV on your maps but
if you want to experiment, it’s good practice!
For your census mapping assignment You can use census data you find from GIS
clearinghouses – e.g., MassGIS Instructions for clipping coastal tracts on GIS
Tips and Tutorials web site
ACS and Error
Always be aware of error Have a statement about error if you are
making maps Might be good to visualize the CV as well, at
least as an inset? In tables, include the margin of error It’s your reputation that’s at stake!