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And where are they going!!?!?!?!. Census Training for Librarians Barbara J. Ronningen March 24, 2010. The 2010 Census. The 2010 Census. Why do we take the Census? It’s in the Constitution! When is the Census? April 1, 2010! Who is Counted? Everyone Counts! Is Census Data Confidential?
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Census Training forLibrariansBarbara J. RonningenMarch 24, 2010
The 2010 Census • Why do we take the Census? • It’s in the Constitution! • When is the Census? • April 1, 2010! • Who is Counted? • Everyone Counts! • Is Census Data Confidential? • YES! Your answers are protected by Title 13 of the U.S. Code, Section 9
10 Questions in 10 Minutes! • Age • Gender • Hispanic Origin • Race • Relationship • Tenure • 4 Administrative Questions • Name, Phone number, Do you live elsewhere, Temporary residents
Power, Money, Data • Minnesota has 8 Congressional Districts Could Minnesota lose a seat? • 400 Billion Dollars in federal funding plus undetermined state dollars every year • Data used to plan services, businesses, schools, churches, libraries . . . .
10 Questions in 10 Minutes! • Data from 2010 Census will be limited • Data on income, educational attainment, housing characteristics, etc. will be available from the American Community Survey • See handout
The American Community Survey: What is it? • Nationwide written/mail survey completed by the U.S. Census Bureau • Sent to a sample of households, not all households • Replaces “long form” of decennial census • Conducted every year • Covers the same major topics as “long form” • 2010 Census will be primarily a population count • Provides more current information: annual data rather than every 10 years
ACS Goals • Provide federal, state, local, and tribal governments an information base for the administration and evaluation of programs • Improve the 2010 Census • Provide yearly demographic, social, economic, and housing data that can be compared across states, communities, and population groups
ACS Methodology in Brief • About 250,000 surveys mailed each month • That totals to 3 million annually (14,040 in MN in CY04) • About a 1 in 40 sample; 2000 Census long form: 1 in 6 • Census assigns both household and person weights • Weights bases on multiple factors (see Accuracy of the Data webpage for details) • Summing the weights produces the estimates • Response rate has exceeded 95% thus far (95.4% in MN) • Not 95% of all surveys sent out; subsample is the base • Has required a large amount of phone and personal interviews for those not returning the mail survey • Monthly surveys combined to estimate figures for the year as a whole
ACS Methodology in Brief • No address (housing unit) will be surveyed more than once in 5 years • Response is mandatory like the decennial census • Household sent a pre-notice letter, then the survey, a reminder card, and finally a replacement questionnaire if not returned • Telephone interview attempted if no response • Finally, a personal interview (site visit if vacant) is conducted • Survey is in English but Spanish on request • Phone, personal interviews bilingual in most languages
ACS Methodology--Sampling • The ACS sample design approximates the Census 2000 long form sample design. • Small governmental units such as American Indian reservations and small towns have a larger proportion sampled. • Incorporated areas with less than 1,200 addresses (≈3,000 people) are “oversampled” • Areas with less than 200 addresses (≈500 people) will be sampled at 10% per year or 1 in 2 over five years (like Census 2000) • Also oversample areas with low mail response • Improves accuracy for minority populations
ACS Methodology--Sampling • Group quarters • Group quarters are non-housing units such as dorms, nursing homes, prisons, shelters, etc. • ACS began sampling group quarters in 2006 • ACS samples 2.5% of the group quarters population (that’s 1 in 40)
Switching from Census to ACS Mentality The Census and the ACS differ – SO - we need to change our way of thinking sometimes. • 1. Timeframe • The Census was a point in time estimate (4-1-00); the ACS accumulates 12 months of surveys for a calendar year estimate • We can usually think of annual ACS estimates as centered within that specific calendar year • Not all data is from that calendar year though -- many questions ask “In the last 12 months…”
Switching from Census to ACS Mentality • 2. Some questions and answer choices differ • Change of residence • Census: 5 years ago; ACS: 1 year ago • Relationship to householder • Census: son/daughter categories for natural-born, adopted, and step; ACS: only a son/daughter category • Census: Parent-in-law and son/daughter-in-law categories; ACS: only an “In law” category • 3. Different estimates and how to use them • Year over year comparisons now possible • 3 or 5 year-estimates for less-populated areas
Switching from Census to ACS Mentality • “2 month” rule for residency • Decennial census relies on one “usual” residence • ACS allows multiple • resident of area if staying there 2+ months when contacted • affects winter and summer areas, students • Adjusting of dollar amounts • Census 2000 is a point in time estimate--as of 4-1-00; an item like income is for the “1999 year” • ACS, sending surveys monthly, asks item like income for the “past 12 months” • Example: If interviewed in July 2008, the reference period is from 7/07 to 6/08 • Released data is adjusted using the CPI and expressed in calendar year 2008 dollars
ACS Subject Areas: Demographic • Population and Housing Unit Totals • Sex • Age • Race • Ethnicity (Hispanic origin) • Household type • Household size and relationships • Housing tenure (owning vs. renting)
ACS Subject Areas: Social • School enrollment • Educational attainment • Marital Status • Fertility (women giving birth in the last year) • Item not asked on Census 2000 • Grandparent/grandchildren items • Disability Status • Mobility • Place of birth, ancestry, language spoken
ACS Subject Areas: Economic • Employment/Unemployment • Commuting to Work • Occupation, Industry • Class of worker • (Government, self-employed, etc.) • Income and sources • Poverty • Receipt of food stamps by households • Item not asked on Census 2000 • Health insurance coverage added in 2008
ACS Subject Areas: Housing • Number of units in structure • Year structure built, Year moved into • Rooms, Occupants per room • House characteristics • Vehicles available • Value • Mortgage status and amount • Rental status and amount
Minnesota ACS Data “On the Way” • With full implementation in 2005, all counties are surveyed. However, data release is delayed until the sample is large enough to be accurate. • Annual one-year estimates for areas with 65,000+ people • 3-year aggregate data for areas with 20,000+ people • 5-year aggregate for areas with under 20,000 people
Minnesota ACS Data Currently Available • Statewide data • Minnesota • Congressional Districts • PUMAs • Counties • One-year estimates available for 12 largest counties • 3-year estimates for 35 more counties • Cities • One-year estimates available for 8 largest cities • 3-year estimates available for 44 more cities • MSAs – 9 metropolitan and micropolitan areas
ACS”: Exercise 1 • Find the proportion of Minnesotans living below the poverty line for 2008. • How does this compare with previous years in Minnesota?
ACS: Exercise 2 • Which state has the highest median household income? • How does Minnesota compare? • Is Minnesota’s median household income significantly different than the U.S.?
ACS: Exercise 3 • Which county had the highest median age in Minnesota in 2008? • Was median age in Hennepin County significantly different than median age in Dakota County in 2008?
Multi-year Estimates: Details • Estimates are computed using the geography in place for the most recent year of the period. • Dollar valued data items are inflation adjusted to the most recent year of the period. • Medians are produced using combined data records from all years, not by averaging each year’s median. • 3-year median determined by combining the 3 years of records into one data set and finding the corresponding median.
Point Estimates and Confidence Intervals • The ACS yearly data provide point estimates for various characteristics. ACS data also include a margin of error. • Why? • The ACS is a sample and subject to sampling error. • Is the data representative of the entire population? • The range between the estimate plus or minus the margin of error is called a confidence interval. • ACS displays a 90% confidence interval. • The bounds tell us that we are 90% confident that the figure for the entire population would be in this range if all households were surveyed. • Confidence intervals are wider for smaller populations.
Confidence Interval Example • The 2004 ACS estimate for the percentage of people 25 and over with a high school diploma in Dakota County is 92.5%. • The lower bound is 91.0% and the upper bound is 93.9%. • Thus, we are 90% confident that for the entire Dakota County population, the percentage with a high school diploma is between 91.0 and 93.9%. • HSDDC, 90% = LB ≤ EST ≤ UB • HSDDC, 90% = 91.0 ≤ 92.5 ≤ 93.9 • Note that the point estimate is halfway between the two bounds. (92.5 ± 1.5)
Confidence Interval Exercise 1 • According to the 2008 ACS, how many persons in Minneapolis were Norwegian (point estimate)? Use the Social Profiles (www.census.gov/acs/www/) • What is the 90% confidence interval for persons claiming Norwegian ancestry in Minneapolis? Lower bound Upper Bound
Confidence Interval Exercise 1 • According to the 2003 ACS, how many persons in Minneapolis were Norwegian (point estimate)? 37,909 Use the Social Profiles • What is the 90% confidence interval for persons claiming Norwegian ancestry in Minneapolis? Lower bound – 35,013 Upper Bound – 40,805
Confidence Interval Comparison Let’s take a look at the 2004 poverty rates for Dakota and Hennepin counties. Lower Upper Estimate Bound Bound Hennepin 9.1 7.7 10.5 Dakota 5.3 3.7 6.9 What do these figures tell us? • Which county has a higher poverty rate? • Which county had greater variability? • Is the difference statistically significant?
Confidence Interval for Poverty Rate in Hennepin and Dakota Counties2004 ACS Since the confidence intervals do not overlap, the estimates are significantly different