- What is the Population Count?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Total Administration Salaries?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Access to Exercise Opportunities Rate?
The population rate of change of Pennsylvania was 0.21% in 2014.
Demographics and Population Datasets Involving Pennsylvania
- API bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z
2010 Census Data on population, pop density, age and ethnicity per zip code
- API health.data.ny.gov | Last Updated 2016-06-09T18:39:22.000Z
This dataset contains death counts, crude rates, and adjusted rates by resident county and race/ethnicity. For more information check out: http://www.health.ny.gov/statistics/vital_statistics. The "About" tab contains additional details concerning this dataset.
- API health.data.ny.gov | Last Updated 2016-06-09T18:37:43.000Z
Population data file is provided as an additional reference file when interpreting vital statistics death rates. The population data is derived from the corresponding release of the NCHS annual estimates of "Bridged Race Vintage" which are consistent with the Bureau of the Census estimates from "Vintage" (released in the summer). For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/. The "About" tab contains additional details concerning this dataset.
- API data.pa.gov | Last Updated 2017-07-19T15:40:20.000Z
This is a listing of Federal Information Processing Standard (FIPS) codes for each of the 67 counties in Pennsylvania. Information gathered from census data - https://www.census.gov/geo/reference/codes/cou.html For more technical details : Federal Information Processing Standards Publications (FIPS PUBS) are issued by the National Institute of Standards and Technology (NIST) after approval by the Secretary of Commerce pursuant to Section 111 (d) of the Federal Property and Administrative Services Act of 1949 as amended by the Computer Security Act of 1987, Public Law 100-235. Federal Information Processing Standard (FIPS) 6-4, Counties and Equivalent Entities of the U.S., Its Possessions, and Associated Areas -- 90 Aug 31 , provides the names and codes that represent the counties and other entities treated as equivalent legal and/or statistical subdivisions of the 50 States, the District of Columbia, and the possessions and freely associated areas of the United States. Counties are considered to be the "first-order subdivisions" of each State and statistically equivalent entity, regardless of their local designations (county, parish, borough, etc.).
- API data.pa.gov | Last Updated 2017-10-11T14:05:07.000Z
Agriculture has guided Pennsylvania's economic growth and cultural development and has profoundly shaped the lands and people of the Commonwealth. The 1850 Federal Decennial Census was the first time in history that data was collected on agricultural production at a national scale. The census manuscripts for Pennsylvania were digitized by PHMC from the original documents in the collections of the National Archives and Records Administration. This dataset includes agricultural production data compiled from Schedule 4 - Productions of Agriculture of the 1850 census and aggregated at the county and municipality level. The visualization combines a timeless practice with the latest advancements in technology. The interactive map of Pennsylvania depicting the value of farms and amounts of livestock provides users with a glimpse into agricultural life in 1850.
Vital Statistics Suicide Deaths by Age-Group, Race/Ethnicity, Resident County, Region and Gender: Beginning 2003health.data.ny.gov | Last Updated 2016-06-15T14:12:39.000Z
This dataset contains suicide death counts and adjusted rates by age group, county, region, race/ethnicity, and gender. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/. The "About" tab contains additional details concerning this dataset.
Vital Statistics Deaths by Gender, Age Group, and Race/Ethnicity by Selected Cause of Death: Beginning 2003health.data.ny.gov | Last Updated 2017-08-16T15:11:28.000Z
<strong>NOTE: This dataset will be deleted shortly. The consolidation of data elements will allow users to more effectively and efficiently present and analyze data, while eliminating duplication. The deleted data will be available in the following dataset: https://health.data.ny.gov/Health/Vital-Statistics-Deaths-by-Region-and-Age-Group-by/c3ns-hz2v</strong> This dataset contains death counts and crude rates by gender, age group, race/ethnicity, and selected cause of death. For more information check out: http://www.health.ny.gov/statistics/vital_statistics/.
- API health.data.ny.gov | Last Updated 2017-08-16T15:11:31.000Z
<strong>NOTE: This dataset will be deleted shortly. The consolidation of data elements will allow users to more effectively and efficiently present and analyze data, while eliminating duplication. The deleted data will be available in the following dataset: https://health.data.ny.gov/Health/Vital-Statistics-Deaths-by-Region-and-Age-Group-by/c3ns-hz2v </strong> This dataset contains death counts, crude rates and adjusted rates by region, race/ethnicity, and selected cause of death. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/. The "About" tab contains additional details concerning this dataset.
- API data.pa.gov | Last Updated 2017-08-22T14:59:47.000Z
One of the governor’s goals related to public safety is the Deparment of Corrections will reduce its state correction population by 5% by 2020. DOC overall total population directly drives the Department’s budget. The baseline for the goal is the total population on June 30, 2015. On June 30, 2015, the Pennsylvania Department of Corrections overall population was 50,366. This dataset contains the total number of state corrections population in the Department’s custody at the end of each month, including those in prison, in contracted county jails, in community phases of the State Intermediate Punishment (SIP) program, in Parole Violator Centers (PVCs), and on temporary transfer to other jurisdictions. DOC publishes a Monthly Population Report to the DOC Website (www.cor.pa.gov). The information published to the website includes the data set and breakdown of populations in each institution.
- API data.pa.gov | Last Updated 2017-07-31T18:19:23.000Z
This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.