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Article I of the US Constitution says an enumeration
of the population (census) must be taken every ten
years.
The first census, taken in 1790, counted 4 million
people in the U.S. Census 2010 counted over 308
million.
The most consistent source of
time series demographic data
available for the U.S.
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Distributed 2 questionnaires every 10 years
Short form = data asked of everyone „100%‟
data
◦ Distributed as summary file 1 and 2
◦ Basic demographic data: age, sex, race, Hispanic/Latino
origin, household relationship, residence owned or rented
◦ Provides data at the most detailed geographic breakdowns
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Long form = „sample‟ data asked of every 1 in 6
households
◦ Distributed as summary file 3 and 4
◦ More detailed social and economic characteristics of
residents, physical characteristics of the housing unit, and
financial characteristics of housing.
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Now just the basic demographic questions
are asked (i.e. the previous “short form”)
Sampling of the population on more detailed
topics is now accomplished by the separate
American Community Survey
Allows Decennial Census to focus on
compiling an accurate count of the
population
Census
ACS
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Samples 3 million
households
Data collected every
day
Timely and available
every year
Provides estimates of
characteristics of
population
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Samples 18 million
households
Data mostly collected
between March and
August
Provides population
counts
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2006 ACS includes people living in group
quarters, earlier versions do not
Census - Residency based on “usual
residence” on April 1, 2010
ACS - Residency based on “current residence”
◦ People are surveyed as long as their stay at that
address will exceed 2 months.
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This difference will mostly affect areas where
the population changes seasonally.
1-year estimates
• Went nationwide 2005
• Geographic areas with population ≥ 65,000
3-year estimates
• Start with 2005-2007 data
• Geographic areas with a population ≥ 20,000
5-year estimates
• Start with 2005-2009 data
• Include populations < 20,000
• Down to block group level geography
Blocks
 Smallest units of data tabulation
 Bounded by visible features or legal boundaries
 Numbered uniquely with a four-digit number, which differs over
time
 Size: average about 100 people.
Block Groups
 Groups of blocks within same census tract sharing the same first
block number digit
 Smallest areas for which sample data are available
 Size: range between 600 to 3,000 people
Census Tracts
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Seamless national coverage
65,000 Census tracts across U.S.
Boundaries try to be maintained over time for comparison
Size: range between 1,200 and 8,000 people
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Approximate area representations of the U.S.
Postal Service five-digit Zip Code service areas
Each block that contains addresses is allocated to
a single ZCTA
This is usually based on the most frequently
occurring Zip Code for the addresses within that
block.
2010 ZCTAs better represent actual Zip Code
service areas because prior to creation of the
2010 blocks, the census split blocks that
contained a large number of addresses with
different zip codes
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Boundaries from January 1st of the last year of
the ACS survey are used for reporting.
Example: 2006-2009 ACS uses boundaries as of
January 1, 2009
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The census does not update geographies for
previously released estimates.
For more information see:
http://www.census.gov/acs/www/guidance_f
or_data_users/geography/
Sampling Errors
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Occur when data are
based on a sample of
the population, not the
entire population
The larger the sample,
the greater the
confidence of the
estimate.
Example: 2005-2009
data are more reliable
than 2005 data alone.
Nonsampling Errors
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Result from mistakes
in how the data are
reported or coded,
problems with the
survey, or problems
related to nonresponse
or interviewer bias.
Trained interviewers
are used for the ACS to
reduce bias.
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It provides a measure of how much the values
provided by the ACS could vary from the
actual population values.
This may impact conclusions you can make
as part of your research.
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Measures the variability of an estimate due to
sampling
Estimates from a sample will not equal the
actual population values and SE provides a
quantitative measure of the extent to which
an estimate can be expected to deviate from
the population value.
SE depends on a
population‟s variability and
sample size.
For example, if 80% of the
households have two males, the
SE of the estimate of the average
number of males per household
will be smaller than in another
population where there is more
variation among households in
the number of males.
Households in
Population 1
Households in
Population 2
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The precision of the estimate at a given level
of confidence.
Census standard confidence level is 90%.
Users can calculate MOE for other confidence
levels.
MOE is relative to the size of the estimate.
◦ Larger sample size usually means lower MOE
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MOEs are provided in every ACS data table for
each variable.
In general, the larger the MOE, the less
reliable the estimate.
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Range that is expected to contain the average
value of the characteristic that would result
over all possible samples with a known
probability
Example: if an estimate of 20,000 has an MOE at a
90% confidence level of +/- 2,000, the Confidence
Interval (CI) would range from 18,000 to 22,000
90%
18,000
20,000
Confidence interval
22,000
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Baltimore: Males who have never married =
52.1% +/- 1.7% (at 90% level)
CI = 50.4% to 53.8%
If we actually asked every single male in
Baltimore if they had been married, there is a
90% chance that the actual mean value will
fall between 50.4% and 53.8%
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Provides a measure of the relative amount of
sampling error that is associated with a sample
estimate
A function of the overall sample size and size of
population of interest.
Single-year estimates for small subpopulations
typically have higher CVs.
804
1000
1196
Coefficient of Variation = .1
980
1020
1000
Coefficient of Variation = .01
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Baltimore: 52.1% of males never married.
Using the previous formula, SE=1.033%
CV=(1.033/52.1) x 100
=1.98%
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This is low, indicating the estimate is reliable.
There are no rules about what CV is
considered too high.
X=ACS
estimated
value
2005-2009
5-year
sample
2009
1-year
sample
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Compare ACS estimates based on the same survey year(s)
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Do not use estimates from overlapping years
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Alternatives:
Example: compare 2005-2009 data for Nantucket and Boston
because only 5-year data are available for Nantucket. Do not
compare 2009 Boston data to 2005-2009 Nantucket data.
Example: Compare 2005-2007 to 2008-2010, not 2005-2007 to
2006-2009
◦ Show single year estimates for large counties and combine
remaining counties into a residual. Subtract the large counties
from total data for the state to find the value of the residual.
◦ Use Public Use Microdata Sample (PUMS), which are samples of
raw data from selected areas
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ACS estimates are similar to those obtained
from past decennial census sample data for
most areas and characteristics.
Many variables can be compared, but users
should be aware of changes in the wording of
questions.
For more information consult:
http://www.census.gov/acs/www/guidance_f
or_data_users/comparing_data/
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There is little to compare because the long
form data is no longer part of 2010 decennial
census.
Population data is likely to differ. The ACS
population totals are based on estimates.
Tiger Files:
http://www.census.gov/geo/www/tiger/wwtl
/wwtl.html
Decennial Census (and ACS starting in Fall
2011):
http://factfinder2.census.gov
ACS (these data will be migrated to Factfinder2 during the fall
of 2011):
http://factfinder.census.gov
http://www.census.gov/acs/www/guidance_for
_data_users/handbooks/