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Data provides 2013-2014 undergraduate student enrollment in engineering, biological and biomedical science, mathematics and physical sciences at Pennsylvania’s publicly supported institutions.
Data is collected in the Spring and reported out in the Fall

This data is pulled from the U.S. Census website. This data is for years 2009-2014.
Product: SAHIE File Layout Overview
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 American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates for Health Insurance Coverage in Pennsylvania and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES.

A blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area.

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.

While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015).

The American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty.

An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area.

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.

While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015).

In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period.

Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.

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.

This is a link to the United States Federal Government's Open Data Portal. Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations.

Check out the attachment in the metadata detailing all the Opioid Related datasets contained in this portal.

Data.gov is the federal government’s open data site, and aims to make government more open and accountable. Opening government data increases citizen participation in government, creates opportunities for economic development, and informs decision making in both the private and public sectors.

Links included for Center for Disease Control and Prevention both the business website and their Data and Statistics website.

This dataset is the shapefile for the US House Districts within PA as of 2019.