This dataset contains the number of enrollees in special education for each county and grade level.

This crosswalk links occupations with degree programs to assist in the identification of degree programs that could lead to employment in a given occupation.

This dataset contains the number of enrollees in special education for each county and grade level.

This dataset contains the number of enrollees in each program of every school that reported for the 2015 to current school years.

For additional information on Career and Technical Education visit Career and Technical Education.

Enroll counts equal to, or below 20, are represented using “ ”.

Welcome to Pennsylvania's Innovation Economy Dashboard. This dashboard, along with the report: Pennsylvania's Innovation Economy Annual Report (May 2021), was developed by students at Carnegie Mellon University. The information here focuses on translating new ideas into jobs, developing and maintaining a talented workforce, and connecting workers to jobs--to keep our state prosperous, competitive, and supportive of all Pennsylvanians.

This dataset contains the Industry Certifications offered by each secondary Career and Technical Education (CTE) program for 2016 school year to the current period.

For additional information on Career and Technical Education visit Career and Technical Education.

The Inc. 5000 is an annually released list that tracks the 5,000 companies in the U.S. that are experiencing the highest revenue growth. Of those companies on the 2020 list, 188 are headquartered in PA.
The literature shows that high growth firms (defined as firms experiencing 20% or greater compound annual revenue grown over 3-years) are responsible for a significantly outsized contribution to economic growth and job creation. It also suggests that small, young, and knowledge-based firms are much more likely to achieve the levels of high growth seen on this list.
The Brookings Institute conducted an analysis and general endorsement of the list: https://www.brookings.edu/research/high-growth-firms-and-cities-in-the-us-an-analysis-of-the-inc-5000/
Source: INC 5000, Introducing the 5,000 Fastest-Growing Companies in America

This dataset contains summary information by county on Incidents involving Drug and Alcohol reported use in Schools.
School categories are Public School, Charter, Intermediate, Vo-Tech, Non-Public and other.
The data count fields are suppressed when less than 11.
The data and more information is also published and searchable online on the https://www.education.pa.gov/Schools/safeschools/Pages/default.aspx website under School Safety.
Here are the infraction codes and definitions that are utilized within this report as found within appendix Z of the PIMS manual:
http://www.education.pa.gov/Documents/Teachers-Administrators/PIMS/PIMS%20Manuals/2017-2018%20PIMS%20Manual%20Vol%202.pdf

While STEM graduates aren't the only contributors to PA’s innovation economy, the number of STEM degrees awarded each year serves as a proxy for the labor pool’s interests and its level of skill development and sophistication (Milken 2018 Report).
As businesses grow in PA, they need skilled and well-educated workers who are prepared for the innovation economy. STEM degree programs help equip students with the knowledge and skills they need to enter the workforce and be successful in a tech-driven, global economy. (PA Department of Education).
Note about data: This table presents data collected from Title IV institutions in the United States. Prior to 2009-10, the data include only Title IV primarily postsecondary institutions.
Source: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS),Completions component final data (2001-02 - 2017-18) and provisional data(2018-19).

Explanation for the 2020 Survey.

This file will be updated each year. It appears to update sometime in December of each year.

Survey/Program:American Community Survey

Universe:Population 18 years and over

Year:2020

Estimates:5-Year

Table ID:B15001

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.

Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.

Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.

The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities.

Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization.

Explanation of Symbols:

- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.

N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area.

(X) The estimate or margin of error is not applicable or not available.
median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")

median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").

** The margin of error could not be computed because there were an insufficient number of sample observations.

*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.

***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.