In 2022, about 32 percent of 4-year-olds were enrolled in state pre-kindergarten, while six percent of 4-year-olds were enrolled in Head Start in the United States. Head Start is a federal program that promotes the school readiness of children ages birth to five years from low-income families.

In 2021, around 7.87 million children were enrolled in nursery or kindergarten programs in the United States. This is an increase from 1970, when about 4.28 million children were enrolled in pre-primary school programs.

In 2024, around **** percent of children aged three to five had been enrolled in and attended preschool in South Korea, up from around **** percent in the previous year. The enrollment rate has steadily increased in recent years.

In 2023, the enrollment rate in early childhood education for ***** to six years old children in Indonesia amounted to ***** percent. The highest enrollment rate during the period measured was in 2018, at ***** percent.

Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

School enrollment, preprimary (% gross) in Vietnam was reported at 92.45 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Vietnam - School enrollment, preprimary (% gross) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Percentage of total enrollment in pre-primary education, regardless of age, compared to the population of the corresponding age group. The indicator is calculated as the total pre-primary education enrollment, based on the national education cycle, divided by the population of the official age group for this level, expressed as a percentage. The rate can exceed 100% due to early entry, grade repetition, or when the age distribution of pupils extends beyond the official school-age range, especially in countries with near-universal education at this level. Name in source: School enrollment, preprimary (% gross).

This dataset includes enrollment data for Pittsburgh Public Schools. Data is presented by school, feeder pattern / attendance boundary, and by neighborhood. A table also includes data on the number of students attending schools by neighborhood. Data includes preschool students through 12th grade. This data can be very useful in understanding neighborhood-level enrollment patterns, student demographics by neighborhood and school, and can also be used to inform school-community partnerships. Students attending charter, private and parochial schools are not included in this data. Only students enrolled in a Pittsburgh Public School are captured. Totals with fewer than 11 students have been redacted to adhere to School District privacy policies. Data was extracted from the Pittsburgh Public Schools data system in January, 2021. It captures the school where the student was enrolled on October 1st. The neighborhood school the student feeds into based on their address as of the beginning of the 2020-21 school year.

AbstractIn this study, we use data from a cohort of 4,033 Tulsa kindergarten students to investigate the relationship between pre-K enrollment and later college enrollment. Specifically, we test whether participation in the Tulsa Public Schools universal pre-K program and the Tulsa CAP Head Start program predict enrollment in two-year or four-year colleges. We use propensity score weighting with multiply imputed data sets to estimate these associations. We find that college enrollment is 12 percentage points higher for Tulsa pre-K alumni compared with children who did not attend Tulsa pre-K or Head Start. College enrollment is 7.5 percentage points higher for Head Start alumni compared to children who did not attend Head Start or Tulsa pre-K, but this difference is only marginally significant. Although Tulsa pre-K attendance is associated with two-year college enrollment among children from all racial and ethnic backgrounds, only among Black and Hispanic students does it strongly predict four-year college enrollment.

The Ministry of Educations' - Basic Education Statistical Booklet captures national statistics for the Education Sector in totality. This Dataset reveals the Enrolment numbers, GER (Gross Enrollment Rate and Net Enrollment rate (NER) for boys and girls across the 47 counties at Early Childhood Development Education centers.

Source: Table 17 ECDE Enrollment And Enrollment Rates By County

Percentage of children in the official age group for early childhood educational development (typically ages 0 to 3 years) who are enrolled in any level of education, expressed as a percentage of the population of the corresponding age group. Name in source: Net enrolment rate, early childhood educational development programmes, both sexes (%).

Vietnam: Preprimary school enrollment, percent of all eligible children: The latest value from 2021 is 92.45 percent, a decline from 92.76 percent in 2020. In comparison, the world average is 52.40 percent, based on data from 66 countries. Historically, the average for Vietnam from 1977 to 2021 is 52.46 percent. The minimum value, 20.39 percent, was reached in 1977 while the maximum of 100.23 percent was recorded in 2018.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages for school enrollment by education level by State of Georgia in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Pop3P_e

# Population ages 3 and over, 2017

Pop3P_m

# Population ages 3 and over, 2017 (MOE)

InSchool_e

# Population 3 years and over enrolled in school, 2017

InSchool_m

# Population 3 years and over enrolled in school, 2017 (MOE)

InPreSchool_e

# Enrolled in nursery school, preschool, 2017

InPreSchool_m

# Enrolled in nursery school, preschool, 2017 (MOE)

pInPreSchool_e

% Enrolled in nursery school, preschool, 2017

pInPreSchool_m

% Enrolled in nursery school, preschool, 2017 (MOE)

InKindergarten_e

# Enrolled in kindergarten, 2017

InKindergarten_m

# Enrolled in kindergarten, 2017 (MOE)

pInKindergarten_e

% Enrolled in kindergarten, 2017

pInKindergarten_m

% Enrolled in kindergarten, 2017 (MOE)

InElementary_e

# Enrolled in elementary school (grades 1-8), 2017

InElementary_m

# Enrolled in elementary school (grades 1-8), 2017 (MOE)

pInElementary_e

% Enrolled in elementary school (grades 1-8), 2017

pInElementary_m

% Enrolled in elementary school (grades 1-8), 2017 (MOE)

InHS_e

# Enrolled in high school (grades 9-12), 2017

InHS_m

# Enrolled in high school (grades 9-12), 2017 (MOE)

pInHS_e

% Enrolled in high school (grades 9-12), 2017

pInHS_m

% Enrolled in high school (grades 9-12), 2017 (MOE)

InCollegeGradSch_e

# Enrolled in college or graduate school, 2017

InCollegeGradSch_m

# Enrolled in college or graduate school, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

Ecuador Consumer Price Index (CPI): Education: PP: Enrollment of Preschool and Primary Education (EE) data was reported at 142.694 2004=100 in Dec 2014. This stayed constant from the previous number of 142.694 2004=100 for Nov 2014. Ecuador Consumer Price Index (CPI): Education: PP: Enrollment of Preschool and Primary Education (EE) data is updated monthly, averaging 121.230 2004=100 from Jan 2005 (Median) to Dec 2014, with 120 observations. The data reached an all-time high of 142.888 2004=100 in Sep 2014 and a record low of 94.212 2004=100 in Mar 2005. Ecuador Consumer Price Index (CPI): Education: PP: Enrollment of Preschool and Primary Education (EE) data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.I016: Consumer Price Index: 2004=100.

"Enrollment counts are based on the October 31 Audited Register for the 2017-18 to 2019-20 school years. To account for the delay in the start of the school year, enrollment counts are based on the November 13 Audited Register for 2020-21 and the November 12 Audited Register for 2021-22. * Please note that October 31 (and November 12-13) enrollment is not audited for charter schools or Pre-K Early Education Centers (NYCEECs). Charter schools are required to submit enrollment as of BEDS Day, the first Wednesday in October, to the New York State Department of Education." Enrollment counts in the Demographic Snapshot will likely exceed operational enrollment counts due to the fact that long-term absence (LTA) students are excluded for funding purposes. Data on students with disabilities, English Language Learners, students' povery status, and students' Economic Need Value are as of the June 30 for each school year except in 2021-22. Data on SWDs, ELLs, Poverty, and ENI in the 2021-22 school year are as of March 7, 2022. 3-K and Pre-K enrollment totals include students in both full-day and half-day programs. Four-year-old students enrolled in Family Childcare Centers are categorized as 3K students for the purposes of this report. All schools listed are as of the 2021-22 school year. Schools closed before 2021-22 are not included in the school level tab but are included in the data for citywide, borough, and district. Programs and Pre-K NYC Early Education Centers (NYCEECs) are not included on the school-level tab. Due to missing demographic information in rare cases at the time of the enrollment snapshot, demographic categories do not always add up to citywide totals. Students with disabilities are defined as any child receiving an Individualized Education Program (IEP) as of the end of the school year (or March 7 for 2021-22). NYC DOE "Poverty" counts are based on the number of students with families who have qualified for free or reduced price lunch, or are eligible for Human Resources Administration (HRA) benefits. In previous years, the poverty indicator also included students enrolled in a Universal Meal School (USM), where all students automatically qualified, with the exception of middle schools, D75 schools and Pre-K centers. In 2017-18, all students in NYC schools became eligible for free lunch. In order to better reflect free and reduced price lunch status, the poverty indicator does not include student USM status, and retroactively applies this rule to previous years. "The school’s Economic Need Index is the average of its students’ Economic Need Values. The Economic Need Index (ENI) estimates the percentage of students facing economic hardship. The 2014-15 school year is the first year we provide ENI estimates. The metric is calculated as follows: * The student’s Economic Need Value is 1.0 if: o The student is eligible for public assistance from the NYC Human Resources Administration (HRA); o The student lived in temporary housing in the past four years; or o The student is in high school, has a home language other than English, and entered the NYC DOE for the first time within the last four years. * Otherwise, the student’s Economic Need Value is based on the percentage of families (with school-age children) in the student’s census tract whose income is below the poverty level, as estimated by the American Community Survey 5-Year estimate (2020 ACS estimates were used in calculations for 2021-22 ENI). The student’s Economic Need Value equals this percentage divided by 100.

Due to differences in the timing of when student demographic, address and census data were pulled, ENI values may vary, slightly, from the ENI values reported in the School Quality Reports.

In previous years, student census tract data was based on students’ addresses at the time of ENI calculation. Beginning in 2018-19, census tract data is based on students’ addresses as of the Audited Register date of the given school year.

In previous years, the most recent new entry date was used for students with multiple entry dates into the NYCDOE. Beginning in 2018-19, students’ earliest entry date is used in ENI calculations.

Beginning in 2018-19, students missing ENI data are imputed with the average ENI at their school. " In order to maintain student privacy, schools with % Poverty and ENI values below 5% or above 95% have had their exact values for each category replaced with "Below 5%" and "Above 95%", respectively. Before the start of the 2017-18 school year, the New York State Education Department implemented a new data matching process that refined the methods to identify families eligible for free lunch. This new matching system provides a more efficient and accurate process for matching students across a range of forms that families already complete. This new matching process yielded an increase in the number of students directly certified for free lunch (in other words, matched to another government program) and therefore increased the direct certification rate. As such, the increase in the percent of students in poverty and the Economic Need Index for the 2017-18 school year and later reflects this new matching process, which allows the City to better identify students eligible for free lunch. Approximately 25% of charter schools in NYC do not use NYC DOE School Food to provide meal services. The NYC DOE Office of School Food does not collect documentation on students’ eligibility for Free or Reduced Price Lunch from schools that do not utilize NYC DOE School Food. As a result, the Poverty figures may be understated for approximately 25% of charter schools. New York State Education Department begins administering assessments to be identified as an English Language Learner (ELL) in Kindergarten, but students in Pre-K are still included in the denominator for the ELL calculations. Also, Pre-K NYC Early Education Centers do not use NYC DOE School Food to provide meal services, but are included in the denominator for Poverty calculations.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages for school enrollment by education level by Strong, Prosperous, And Resilient Communities Challenge in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Pop3P_e

# Population ages 3 and over, 2017

Pop3P_m

# Population ages 3 and over, 2017 (MOE)

InSchool_e

# Population 3 years and over enrolled in school, 2017

InSchool_m

# Population 3 years and over enrolled in school, 2017 (MOE)

InPreSchool_e

# Enrolled in nursery school, preschool, 2017

InPreSchool_m

# Enrolled in nursery school, preschool, 2017 (MOE)

pInPreSchool_e

% Enrolled in nursery school, preschool, 2017

pInPreSchool_m

% Enrolled in nursery school, preschool, 2017 (MOE)

InKindergarten_e

# Enrolled in kindergarten, 2017

InKindergarten_m

# Enrolled in kindergarten, 2017 (MOE)

pInKindergarten_e

% Enrolled in kindergarten, 2017

pInKindergarten_m

% Enrolled in kindergarten, 2017 (MOE)

InElementary_e

# Enrolled in elementary school (grades 1-8), 2017

InElementary_m

# Enrolled in elementary school (grades 1-8), 2017 (MOE)

pInElementary_e

% Enrolled in elementary school (grades 1-8), 2017

pInElementary_m

% Enrolled in elementary school (grades 1-8), 2017 (MOE)

InHS_e

# Enrolled in high school (grades 9-12), 2017

InHS_m

# Enrolled in high school (grades 9-12), 2017 (MOE)

pInHS_e

% Enrolled in high school (grades 9-12), 2017

pInHS_m

% Enrolled in high school (grades 9-12), 2017 (MOE)

InCollegeGradSch_e

# Enrolled in college or graduate school, 2017

InCollegeGradSch_m

# Enrolled in college or graduate school, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages for school enrollment by education level by Westside Future Fund in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Pop3P_e

# Population ages 3 and over, 2017

Pop3P_m

# Population ages 3 and over, 2017 (MOE)

InSchool_e

# Population 3 years and over enrolled in school, 2017

InSchool_m

# Population 3 years and over enrolled in school, 2017 (MOE)

InPreSchool_e

# Enrolled in nursery school, preschool, 2017

InPreSchool_m

# Enrolled in nursery school, preschool, 2017 (MOE)

pInPreSchool_e

% Enrolled in nursery school, preschool, 2017

pInPreSchool_m

% Enrolled in nursery school, preschool, 2017 (MOE)

InKindergarten_e

# Enrolled in kindergarten, 2017

InKindergarten_m

# Enrolled in kindergarten, 2017 (MOE)

pInKindergarten_e

% Enrolled in kindergarten, 2017

pInKindergarten_m

% Enrolled in kindergarten, 2017 (MOE)

InElementary_e

# Enrolled in elementary school (grades 1-8), 2017

InElementary_m

# Enrolled in elementary school (grades 1-8), 2017 (MOE)

pInElementary_e

% Enrolled in elementary school (grades 1-8), 2017

pInElementary_m

% Enrolled in elementary school (grades 1-8), 2017 (MOE)

InHS_e

# Enrolled in high school (grades 9-12), 2017

InHS_m

# Enrolled in high school (grades 9-12), 2017 (MOE)

pInHS_e

% Enrolled in high school (grades 9-12), 2017

pInHS_m

% Enrolled in high school (grades 9-12), 2017 (MOE)

InCollegeGradSch_e

# Enrolled in college or graduate school, 2017

InCollegeGradSch_m

# Enrolled in college or graduate school, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages for school enrollment by education level by Zip Code Tabulation Area in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Pop3P_e

# Population ages 3 and over, 2017

Pop3P_m

# Population ages 3 and over, 2017 (MOE)

InSchool_e

# Population 3 years and over enrolled in school, 2017

InSchool_m

# Population 3 years and over enrolled in school, 2017 (MOE)

InPreSchool_e

# Enrolled in nursery school, preschool, 2017

InPreSchool_m

# Enrolled in nursery school, preschool, 2017 (MOE)

pInPreSchool_e

% Enrolled in nursery school, preschool, 2017

pInPreSchool_m

% Enrolled in nursery school, preschool, 2017 (MOE)

InKindergarten_e

# Enrolled in kindergarten, 2017

InKindergarten_m

# Enrolled in kindergarten, 2017 (MOE)

pInKindergarten_e

% Enrolled in kindergarten, 2017

pInKindergarten_m

% Enrolled in kindergarten, 2017 (MOE)

InElementary_e

# Enrolled in elementary school (grades 1-8), 2017

InElementary_m

# Enrolled in elementary school (grades 1-8), 2017 (MOE)

pInElementary_e

% Enrolled in elementary school (grades 1-8), 2017

pInElementary_m

% Enrolled in elementary school (grades 1-8), 2017 (MOE)

InHS_e

# Enrolled in high school (grades 9-12), 2017

InHS_m

# Enrolled in high school (grades 9-12), 2017 (MOE)

pInHS_e

% Enrolled in high school (grades 9-12), 2017

pInHS_m

% Enrolled in high school (grades 9-12), 2017 (MOE)

InCollegeGradSch_e

# Enrolled in college or graduate school, 2017

InCollegeGradSch_m

# Enrolled in college or graduate school, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

The average for 2020 based on 136 countries was 72.38 percent. The highest value was in Australia: 160.21 percent and the lowest value was in Micronesia: 5.96 percent. The indicator is available from 1970 to 2022. Below is a chart for all countries where data are available.

This dataset contains student enrollment data for all Massachusetts public schools and districts since 1994. It is a wide file with three groups of columns representing the following enrollment indicators:

• Number of students by grade, including pre-kindergarten (PK), kindergarten (K) and special education beyond 12th grade (SP)
• Percent of students by race and gender
• Number and percent of students in student groups: First Language Not English, English Learners, Students with Disabilities, High Needs, Low Income, and Economically Disadvantaged

This dataset contains the same data that is also published on our DESE Profiles site: Enrollment by Grade https://profiles.doe.mass.edu/statereport/enrollmentbyracegender.aspx" target="_blank" rel="noreferrer noopener">Enrollment by Race/Gender Enrollment by Selected Population