Costa Rica CR: Primary School Starting Age data was reported at 6.000 Year in 2023. This stayed constant from the previous number of 6.000 Year for 2022. Costa Rica CR: Primary School Starting Age data is updated yearly, averaging 6.000 Year from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 6.000 Year in 2023 and a record low of 6.000 Year in 2023. Costa Rica CR: Primary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Social: Education Statistics. Primary school starting age is the age at which students would enter primary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

The 2012 Beginning Postsecondary Students Longitudinal Study, 2012 Base Year (BPS:12) is part of the Beginning Postsecondary Students Longitudinal Study (BPS) program. BPS:12 is the base year of a longitudinal study that followed a cohort of students who enrolled in postsecondary education for the first time during the 2011–12 academic year, irrespective of date of high school completion. The 2012–13 National Postsecondary Student Aid Study (NPSAS:12) data provided the base-year sample for BPS:12. BPS:12 data are representative of all first-time beginning (FTB) students enrolled in postsecondary institutions in the 50 United States and the District of Columbia that were eligible to participate in the federal financial aid programs in Title IV of the Higher Education Act. The cohort includes a subset of students initially sampled for participation in NPSAS:12 and classified by their NPSAS institution as FTBs. Key statistics produced from BPS:12 are data on student persistence in, and completion of, postsecondary education programs; their transition to employment; demographic characteristics; and changes over time in their goals, marital status, income, and debt, among other measures.

Since the beginning of the 1960s, Statistics Sweden, in collaboration with various research institutions, has carried out follow-up surveys in the school system. These surveys have taken place within the framework of the IS project (Individual Statistics Project) at the University of Gothenburg and the UGU project (Evaluation through follow-up of students) at the University of Teacher Education in Stockholm, which since 1990 have been merged into a research project called 'Evaluation through Follow-up'. The follow-up surveys are part of the central evaluation of the school and are based on large nationally representative samples from different cohorts of students.

Evaluation through follow-up (UGU) is one of the country's largest research databases in the field of education. UGU is part of the central evaluation of the school and is based on large nationally representative samples from different cohorts of students. The longitudinal database contains information on nationally representative samples of school pupils from ten cohorts, born between 1948 and 2004. The sampling process was based on the student's birthday for the first two and on the school class for the other cohorts.

For each cohort, data of mainly two types are collected. School administrative data is collected annually by Statistics Sweden during the time that pupils are in the general school system (primary and secondary school), for most cohorts starting in compulsory school year 3. This information is provided by the school offices and, among other things, includes characteristics of school, class, special support, study choices and grades. Information obtained has varied somewhat, e.g. due to changes in curricula. A more detailed description of this data collection can be found in reports published by Statistics Sweden and linked to datasets for each cohort.

Survey data from the pupils is collected for the first time in compulsory school year 6 (for most cohorts). Questionnaire in survey in year 6 includes questions related to self-perception and interest in learning, attitudes to school, hobbies, school motivation and future plans. For some cohorts, questionnaire data are also collected in year 3 and year 9 in compulsory school and in upper secondary school.

Furthermore, results from various intelligence tests and standartized knowledge tests are included in the data collection year 6. The intelligence tests have been identical for all cohorts (except cohort born in 1987 from which questionnaire data were first collected in year 9). The intelligence test consists of a verbal, a spatial and an inductive test, each containing 40 tasks and specially designed for the UGU project. The verbal test is a vocabulary test of the opposite type. The spatial test is a so-called ‘sheet metal folding test’ and the inductive test are made up of series of numbers. The reliability of the test, intercorrelations and connection with school grades are reported by Svensson (1971).

For the first three cohorts (1948, 1953 and 1967), the standartized knowledge tests in year 6 consist of the standard tests in Swedish, mathematics and English that up to and including the beginning of the 1980s were offered to all pupils in compulsory school year 6. For the cohort 1972, specially prepared tests in reading and mathematics were used. The test in reading consists of 27 tasks and aimed to identify students with reading difficulties. The mathematics test, which was also offered for the fifth cohort, (1977) includes 19 assignments. After a changed version of the test, caused by the previously used test being judged to be somewhat too simple, has been used for the cohort born in 1982. Results on the mathematics test are not available for the 1987 cohort. The mathematics test was not offered to the students in the cohort in 1992, as the test did not seem to fully correspond with current curriculum intentions in mathematics. For further information, see the description of the dataset for each cohort.

For several of the samples, questionnaires were also collected from the students 'parents and teachers in year 6. The teacher questionnaire contains questions about the teacher, class size and composition, the teacher's assessments of the class' knowledge level, etc., school resources, working methods and parental involvement and questions about the existence of evaluations. The questionnaire for the guardians includes questions about the child's upbringing conditions, ambitions and wishes regarding the child's education, views on the school's objectives and the parents' own educational and professional situation.

The students are followed up even after they have left primary school. Among other things, data collection is done during the time they are in high school. Then school administrative data such as e.g. choice of upper secondary school line / program and grades after completing studies. For some of the cohorts, in addition to school administrative data, questionnaire data were also collected from the students.

he sample consisted of students born on the 5th, 15th and 25th of any month in 1953, a total of 10,723 students.

The data obtained in 1966 were: 1. School administrative data (school form, class type, year and grades). 2. Information about the parents' profession and education, number of siblings, the distance between home and school, etc.

This information was collected for 93% of all born on the current days. The reason for this is reduced resources for Statistics Sweden for follow-up work - reminders etc. Annual data for cohorts in 1953 were collected by Statistics Sweden up to and including academic year 1972/73.

1. Answers to certain questions that shed light on students' school motivation, leisure activities and study and career plans. Some of the questions changed significantly compared to the cohort in 1948 due to the fact that they did not function satisfactorily from a metrological point of view.
2. Results on three aptitude tests, one verbal, one spatial and one inductive.
3. Standard test results in reading, writing, mathematics and English, which were offered to the students who belonged to year 6.

Response rate for test and questionnaire data is 88% Standard test results were received for just over 85% of those who took the tests.

The sample included a total of 9955 students, for whom some form of information was obtained.

Part of the "Individual Statistics Project" together with cohort 1953.

Historical Dataset of Head Start is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2005-2023),Total Classroom Teachers Trends Over Years (2010-2014),Asian Student Percentage Comparison Over Years (2005-2023),Hispanic Student Percentage Comparison Over Years (2005-2023),Black Student Percentage Comparison Over Years (2005-2023),White Student Percentage Comparison Over Years (2005-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (2005-2023),Free Lunch Eligibility Comparison Over Years (2007-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2008-2023)

San Marino Primary School Starting Age data was reported at 6.000 Year in 2017. This stayed constant from the previous number of 6.000 Year for 2016. San Marino Primary School Starting Age data is updated yearly, averaging 6.000 Year from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 6.000 Year in 2017 and a record low of 6.000 Year in 2017. San Marino Primary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s San Marino – Table SM.World Bank.WDI: Education Statistics. Primary school starting age is the age at which students would enter primary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.; ; UNESCO Institute for Statistics; ;

Overall attendance data include students in Districts 1-32 and 75 (Special Education). Students in District 79 (Alternative Schools & Programs), charter schools, home schooling, and home and hospital instruction are excluded. Pre-K data do not include NYC Early Education Centers or District Pre-K Centers; therefore, Pre-K data are limited to those who attend K-12 schools that offer Pre-K. Transfer schools are included in citywide, borough, and district counts but removed from school-level files. Attendance is attributed to the school the student attended at the time. If a student attends multiple schools in a school year, the student will contribute data towards multiple schools. Starting in 2020-21, the NYC DOE transitioned to NYSED's definition of chronic absenteeism. Students are considered chronically absent if they have an attendance of 90 percent or less (i.e. students who are absent 10 percent or more of the total days). In order to be included in chronic absenteeism calculations, students must be enrolled for at least 10 days (regardless of whether present or absent) and must have been present for at least 1 day. The NYSED chronic absenteeism definition is applied to all prior years in the report. School-level chronic absenteeism data reflect chronic absenteeism at a particular school. In order to eliminate double-counting students in chronic absenteeism counts, calculations at the district, borough, and citywide levels include all attendance data that contribute to the given geographic category. For example, if a student was chronically absent at one school but not at another, the student would only be counted once in the citywide calculation. For this reason, chronic absenteeism counts will not align across files. All demographic data are based on a student's most recent record in a given year. Students With Disabilities (SWD) data do not include Pre-K students since Pre-K students are screened for IEPs only at the parents' request. English language learner (ELL) data do not include Pre-K students since the New York State Education Department only begins administering assessments to be identified as an ELL in Kindergarten. Only grades PK-12 are shown, but calculations for "All Grades" also include students missing a grade level, so PK-12 may not add up to "All Grades". Data include students missing a gender, but are not shown due to small cell counts. Data for Asian students include Native Hawaiian or Other Pacific Islanders . Multi-racial and Native American students, as well as students missing ethnicity/race data are included in the "Other" ethnicity category. In order to comply with the Family Educational Rights and Privacy Act (FERPA) regulations on public reporting of education outcomes, rows with five or fewer students are suppressed, and have been replaced with an "s". Using total days of attendance as a proxy , rows with 900 or fewer total days are suppressed. In addition, other rows have been replaced with an "s" when they could reveal, through addition or subtraction, the underlying numbers that have been redacted. Chronic absenteeism values are suppressed, regardless of total days, if the number of students who contribute at least 20 days is five or fewer. Due to the COVID-19 pandemic and resulting shift to remote learning in March 2020, 2019-20 attendance data was only available for September 2019 through March 13, 2020. Interactions data from the spring of 2020 are reported on a separate tab. Interactions were reported by schools during remote learning, from April 6 2020 through June 26 2020 (a total of 57 instructional days, excluding special professional development days of June 4 and June 9). Schools were required to indicate any student from their roster that did not have an interaction on a given day. Schools were able to define interactions in a way that made sense for their students and families. Definitions of an interaction included: • Student submission of an assignment or completion of an

Every four years in the United States, the electoral college system is used to determine the winner of the presidential election. In this system, each state has a fixed number of electors based on their population size, and (generally speaking) these electors then vote for their candidate with the most popular votes within their state or district. Since 1964, there have been 538 electoral votes available for presidential candidates, who need a minimum of 270 votes to win the election. Because of this system, candidates do not have to win over fifty percent of the popular votes across the country, but just win in enough states to receive a total of 270 electoral college votes. Popular results From 1789 until 1820, there was no popular vote, and the President was then chosen only by the electors from each state. George Washington was unanimously voted for by the electorate, receiving one hundred percent of the votes in both elections. From 1824, a popular vote has been conducted among American citizens (with varying levels of access for women, Blacks, and poor voters), to help electors in each state decide who to vote for (although the 1824 winner was chosen by the House of Representatives, as no candidate received over fifty percent of electoral votes). Since 1924, the difference in the share of both votes has varied, with several candidates receiving over 90 percent of the electoral votes while only receiving between fifty and sixty percent of the popular vote. The highest difference was for Ronald Reagan in 1980, where he received just 50.4 percent of the popular vote, but 90.9 percent of the electoral votes. Unpopular winners Since 1824, there have been 51 elections, and in 19 of these the winner did not receive over fifty percent of the popular vote. In the majority of these cases, the winner did receive a plurality of the votes, however there have been five instances where the winner of the electoral college vote lost the popular vote to another candidate. The most recent examples of this were in 2000, when George W. Bush received roughly half a million fewer votes than Al Gore, and in 2016, where Hillary Clinton won approximately three million more votes than Donald Trump.

Primary school starting age (years) in Monaco was reported at 6 years in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Monaco - Primary school starting age (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

This dataset contains unemployment data at metropolitan area (MA) level, respectively the change over the year of unemployment rate. The data for the unemployment rate change over the year is starting from 2023 to 2024.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

Historical Dataset of Head Start Program is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2003-2023),Total Classroom Teachers Trends Over Years (1999-2023),Student-Teacher Ratio Comparison Over Years (2003-2023),Asian Student Percentage Comparison Over Years (2003-2023),Hispanic Student Percentage Comparison Over Years (2003-2023),Black Student Percentage Comparison Over Years (2003-2023),White Student Percentage Comparison Over Years (2003-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (2003-2023),Free Lunch Eligibility Comparison Over Years (2007-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2006-2008)

Portugal PT: Primary School Starting Age data was reported at 6.000 Year in 2017. This stayed constant from the previous number of 6.000 Year for 2016. Portugal PT: Primary School Starting Age data is updated yearly, averaging 6.000 Year from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 7.000 Year in 1970 and a record low of 6.000 Year in 2017. Portugal PT: Primary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Portugal – Table PT.World Bank.WDI: Education Statistics. Primary school starting age is the age at which students would enter primary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.; ; UNESCO Institute for Statistics; ;

Historical Dataset of Psja Early Start is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2011-2023),Total Classroom Teachers Trends Over Years (2011-2023),Student-Teacher Ratio Comparison Over Years (2011-2023),Hispanic Student Percentage Comparison Over Years (2011-2023),White Student Percentage Comparison Over Years (2011-2023),Diversity Score Comparison Over Years (2011-2023),Free Lunch Eligibility Comparison Over Years (2013-2023)

Georgia GE: Primary School Starting Age data was reported at 6.000 Year in 2017. This stayed constant from the previous number of 6.000 Year for 2016. Georgia GE: Primary School Starting Age data is updated yearly, averaging 6.000 Year from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 6.000 Year in 2017 and a record low of 6.000 Year in 2017. Georgia GE: Primary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Education Statistics. Primary school starting age is the age at which students would enter primary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.; ; UNESCO Institute for Statistics; ;

About this dataset

Context

The dataset tabulates the Early population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Early. The dataset can be utilized to understand the population distribution of Early by age. For example, using this dataset, we can identify the largest age group in Early.

Key observations

The largest age group in Early, IA was for the group of age 60 to 64 years years with a population of 98 (12.45%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Early, IA was the 75 to 79 years years with a population of 9 (1.14%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Early is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Early total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Early Population by Age. You can refer the same here

IZG 200. General schools by statistical region and cities under state jurisdiction at the beginning of the school year

Key Table Information.Table Title.Selected Sectors: Sales, Value of Shipments, or Revenue Size of Firms for the U.S.: 2022.Table ID.ECNSIZE2022.EC2200SIZEREVFIRM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Economic Census: Establishment and Firm Size Statistics for the U.S..Source.U.S. Census Bureau, 2022 Economic Census, Core Statistics.Release Date.2025-04-24.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of firmsNumber of establishmentsSales, value of shipments, or revenue ($1,000)Annual payroll ($1,000)First-quarter payroll ($1,000)Number of employeesOperating expenses ($1,000)Total inventories, beginning of year ($1,000)Total inventories, end of year ($1,000)Range indicating imputed percentage of total sales, value of shipments, or revenueRange indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. levels only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels for all economic census sectors except Agriculture (11) and Management of Companies and Enterprises (55). For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction ar...