Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Living quarters

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Group quarters: Yes - Special populations: No

UNIT DESCRIPTIONS: - Group quarters: Living quarters which is built or converted for living (e.g. house, flat, apartment, shophouse, makeshift hut, hotel, hostels, etc.).

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Department of Statistics, Malaysia

SAMPLE FRACTION: 2%

SAMPLE SIZE (person records): 175,997

Mode of data collection

Face-to-face [f2f]

Research instrument

Five separate forms constitute the total questionnaire. There was a House Listing Book, a Living Quarters Form, an Agricultural Census Form, a Household Census Form and a Persons Form. For ease of reference those were designated as Forms 1, 2, 3, 4, and 5 respectively.

Response rate

UNDERCOUNT: 100%

Geolytics Census 2000 Long Form dataset. The Geolytics Census 2000 Long Form is a comprehensive source of detailed information about the people, housing, and economy of the United States. The Census 2000 Long Form offers the entire US Census Bureau's SF3 dataset. This dataset contains variables such as income, housing, employment, language spoken, ancestry, education, poverty, rent, mortgage, commute to work, etc. There are 5,500 variables at the Block Group level. A select portion of the Geolytics Census data was joined to GDT spatial data by block group and some census attributes were aggregated. See the attached txt file for a description of the attributes. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Abstract

For more than 150 years, the U.S. Department of Commerce, Bureau of the Census, conducted the census of agriculture. However, the 2002 Appropriations Act transferred the responsibility from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture for the U.S. Virgin Islands is the second census in the U.S. Virgin Islands conducted by NASS. The census of agriculture is taken to obtain agricultural statistics for each county, State (including territories and protectorates), and the Nation. The first U.S. agricultural census data were collected in 1840 as a part of the sixth decennial census. From 1840 to 1920, an agricultural census was taken as a part of each decennial census. Since 1920, a separate national agricultural census has been taken every 5 years. The 2007 census is the 14th census of agriculture of the U.S. Virgin Islands. The first, taken in 1920, was a special census authorized by the Secretary of Commerce. The next agriculture census was taken in 1930 in conjunction with the decennial census, a practice that continued every 10 years through 1960. The 1964 Census of Agriculture was the first quinquennial (5-year) census to be taken in the U.S. Virgin Islands. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data-reference year to coincide with the 1982 Economic Censuses covering manufacturing, mining, construction, retail trade, wholesale trade, service industries, and selected transportation activities. After 1982, the agriculture census reverted to a 5-year cycle. Data in this publication are for the calendar year 2007, and inventory data reflect what was on hand on December 31, 2007. This is the same reference period used in the 2002 census. Prior to the 2002 census, data was collected in the summer for the previous 12 months, with inventory items counted as what was on hand as of July 1 of the year the data collection was done.

Objectives: The census of agriculture is the leading source of statistics about the U.S. Virgin Islands’s agricultural production and the only source of consistent, comparable data at the island level. Census statistics are used to measure agricultural production and to identify trends in an ever changing agricultural sector. Many local programs use census data as a benchmark for designing and evaluating surveys. Private industry uses census statistics to provide a more effective production and distribution system for the agricultural community.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was a farm, defined as "any place from which USD 500 or more of agricultural products were produced and sold, or normally would had been sold, during the calendar year 2007". According to the census definition, a farm is essentially an operating unit, not an ownership tract. All land operated or managed by one person or partnership represents one farm. In the case of tenants, the land assigned to each tenant is considered a separate farm, even though the landlord may consider the entire landholding to be one unit rather than several separate units.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Method of Enumeration As in the previous censuses of the U.S. Virgin Islands, a direct enumeration procedure was used in the 2007 Census of Agriculture. Enumeration was based on a list of farm operators compiled by the U.S. Virgin Islands Department of Agriculture. This list was compiled with the help of the USDA Farm Services Agency located in St. Croix. The statistics in this report were collected from farm operators beginning in January of 2003. Each enumerator was assigned a list of individuals or farm operations from a master enumeration list. The enumerators contacted persons or operations on their list and completed a census report form for all farm operations. If the person on the list was not operating a farm, the enumerator recorded whether the land had been sold or rented to someone else and was still being used for agriculture. If land was sold or rented out, the enumerator got the name of the new operator and contacted that person to ensure that he or she was included in the census.

(b) Frame The census frame consisted of a list of farm operators compiled by the U.S. Virgin Islands DA. This list was compiled with the help of the USDA Farm Services Agency, located in St. Croix.

(c) Complete and/or sample enumeration methods The census was a complete enumeration of all farm operators registered in the list compiled by the United States of America in the CA 2007.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire (report form) for the CA 2007 was prepared by NASS, in cooperation with the DA of the U.S. Virgin Islands. Only one questionnaire was used for data collection covering topics on:

• Land owned
• Land use
• Irrigation
• Conservation programs and crop insurance
• Field crops
• Bananas, coffee, pineapples and plantain crops
• Hay and forage crops
• Nursery, Greenhouse, Floriculture, Sod and tree seedlings
• Vegetables and melons
• Hydroponic crops
• Fruit
• Root crops
• Cattle and calves
• Poultry
• Hogs and pigs
• Aquaculture
• Other animals and livestock products
• Value of sales
• Organic agriculture
• Federal and commonwealth agricultural program payments
• Income from farm-related sources
• Production expenses
• Farm labour
• Fertilizer and chemicals applied
• Market value of land and buildings
• Machinery, equipment and buildings
• Practices
• Type of organization
• Operator characteristics

The questionnaire of the 2007 CA covered 12 of the 16 core items' recommended for the WCA 2010 round.

Cleaning operations

DATA PROCESSING The processing of the 2007 Census of Agriculture for the U.S. Virgin Islands was done in St. Croix. Each report form was reviewed and coded prior to data keying. Report forms not meeting the census farm definition were voided. The remaining report forms were examined for clarity and completeness. Reporting errors in units of measures, illegible entries, and misplaced entries were corrected. After all the report forms had been reviewed and coded, the data were keyed and subjected to a thorough computer edit. The edit performed comprehensive checks for consistency and reasonableness, corrected erroneous or inconsistent data, supplied missing data based on similar farms, and assigned farm classification codes necessary for tabulating the data. All substantial changes to the data generated by the computer edits were reviewed and verified by analysts. Inconsistencies identified, but not corrected by the computer, were reviewed, corrected, and keyed to a correction file. The corrected data were then tabulated by the computer and reviewed by analysts. Prior to publication, tabulated totals were reviewed by analysts to identify inconsistencies and potential coverage problems. Comparisons were made with previous census data, as well as other available data. The computer system provided the capability to review up-to-date tallies of all selected data items for various sets of criteria which included, but were not limited to, geographic levels, farm types, and sales levels. Data were examined for each set of criteria and any inconsistencies or potential problems were then researched by examining individual data records contributing to the tabulated total. W hen necessary, data inconsistencies were resolved by making corrections to individual data records.

Sampling error estimates

The accuracy of these tabulated data is determined by the joint effects of the various nonsampling errors. No direct measures of these effects have been obtained; however, precautionary steps were taken in all phases of data collection, processing, and tabulation of the data in an effort to minimize the effects of nonsampling errors.

Abstract

Agriculture significantly contributes to Indonesia’s economy. Up to 2013, this sector is the second largest contribution behind manufacturing industry sector, even though the value of the contribution keeps declining from time to time. However, the interesting fact is that approximately a third of total labor force depends on this sector (National Labor Force Survey, August 2013). To develop agriculture sector requires detailed and accurate data on various characteristics of agricultural holdings. Therefore, to meet the requirement for the data, BPS (Statistics Indonesia) as the national statistical office has conducted not only surveys but also census on agriculture. Since independence, Indonesia has carried out national agricultural census six times. The first was the 1963 Agricultural Census that might hardly be successful in practice but served as a reference to the next censuses refinement.

Objectives of Agricultural Census 2013:

The data obtained from the census has distinct characteristics compared to the data from annual agricultural surveys. The main purposes of the 2013 Census are as follows:

a. Collecting accurate and comprehensive data that delineate agriculture condition in Indonesia.

b. Building sampling frame to be used for agricultural surveys.

c. Collecting information on agricultural population, peasants or farmers with = 0.5 hectare of farmland), crops and livestock, landowning and cultivation, etc. The result of the 2013 Census will be used as benchmarks for various agricultural surveys.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as an activity producing agricultural products with the aim of partially or completely selling or exchanging the products, except when food crops were exclusively for self-consumption. In general, two types of holdings were covered in the household sector: agricultural production households ("household agricultural holding") and other households ("non-agricultural households").

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Complete Enumeration The 2013 Agricultural Census applied complete enumeration of agricultural households. It was meant to collect data and information on population of agricultural holdings, number of crops and livestock, and farmland area distribution. The result of the census will be used as sampling frame and benchmark for further agricultural surveys.The agricultural census activities also included the surveys that provide supporting data for the census itself. The beginning activity in the implementation stage was updating households and buildings, conducted in May 2013, in order to discover current information on agricultural households in every census block. The result will be in the form of lists that distinguish between agricultural and non-agricultural households. In operation, the census was supported by 246,412 enumerators and team coordinators.

(b) Strategy There were two methods of enumeration, door to door and snowball. Door to door was conducting visit to all households both listed and unlisted in the block census. Area coverage of this method was rural villages and urban villages with the majority of agricultural business (in district) and the areas with the majority of agricultural business (in municipality). Meanwhile, the snowball method was carried out in urban villages with the majority of agricultural business (in district) and urban areas with the majority of nonagricultural business (in municipality). Through the enumeration, it was founded there are 26,135,469 agricultural households.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. The listing of households engaged in the agricultural sector was conducted using the ST2013-P form ("door-to-door" and "snowball").

2. The census questionnaire used the ST2013-L form.

3. Other specific questionnaires were used for collecting information in subsequent surveys as part of the CA 2013 programme:

(i) the Agricultural Household Income Survey, in 2013 (ST2013-SPP.S form) (ii) the Agricultural Households Sub-sector Survey, in 2014 (iii) the Survey of Forestry Households in 2014 (ST2013-SKH form)

The CA 2013 questionnaire covered all 16 core items recommended for the WCA 2010 round, namely;

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

See questionnaire in external materials tab

Cleaning operations

(a) Data Processing Data processing of The 2013 Agricultural Census is a follow-up activity after the enumeration. This activity will produce the intended data in accurate and timely manner. It doing the data processing, it was supported by data capture technologies by scanner machine in all provinces and district/municipalities from June to December 2013. The stages of the data processing were as follows:

1. Pre-computer processing:
2. Document receiving
3. Document batching

4. Editing and coding

5. Computer processing:

6. Data scanning

7. Data tabulation

All data processing used a particular network system in processing center. This network system was made for the census data processing purposes only. It was separated from local and other networking, so it can prevent the large data traffic that could slow down the data processing.

Sampling error estimates

(nonsampling error). Errors made by the enumerators might be in the forms of coverage error (either under-coverage or over-coverage), and content error. Error in completing the questionnaire were mostly derived from the respondents which was called response error.

Data appraisal

PES was conducted immediately after the completion of the data collection process and independently from the census enumeration. This survey sought to determine the level of coverage accuracy, the level of content accuracy in the implementation of the CA 2013, and to facilitate the use of census data by giving deeper insights on the quality and limitations of census data

This map shows the percentage of Black or African American population, alone or in combination with any other race and independent of ethnicity, throughout the US according to the 2020 decennial Census. The people represented in this map chose "Black or African American" alone or in combination with another race in the survey (see the Census form here).For more information about the racial categories included on the 2020 Census, visit this resource from the U.S. Census Bureau. The pattern is shown by states, counties, tracts, block groups, and blocks. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The data is from the decennial 2020 Census, and is sourced by the U.S. Census Bureau for all states plus D.C. and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables. For full metadata including data processing notes, visit this group of ArcGIS Living Atlas layers.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteAdditional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The units of geography used for the 2010 Census maps displayed here are the Census tracts. Census tracts generally have a population size between 1 - 200 and 8 - 000 people - with an optimum size of 4 - 000 people. When first delineated - census tracts were designed to be homogeneous with respect to population characteristics - economic status - and living conditions. Census tract boundaries generally follow visible and identifiable features. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances - a census tract may consist of noncontiguous areas. The data collected on the short form survey are general demographic characteristics such as age - race - ethnicity - household relationship - housing vacancy and tenure (owner/renter).Feature Service Link:http://geodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer/0 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Not available in microdata sample - Vacant units: Not available in microdata sample - Households: Yes - Individuals: Yes - Group quarters: Includes but not identified - Special populations: No special populations

UNIT DESCRIPTIONS: - Households: Each person living alone and each group of related persons living in a single dwelling unit constitutes a household. Unrelated persons living in a single dwelling unit constitute a household if they prepare meals of their meals together. - Group quarters: An administrative unit that provides dormitory facilities and usually food services to at least five individuals.

Universe

Persons who on the census night lived at an address in the area covered, including those found abroad on the census night who had been absent from the area covered for less than one year.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Bureau of Statistics - Israel

SAMPLE DESIGN: Systematic sample of every 5th household after a random start. 1-in-2 sample drawn from that by MPC.

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 403,474

Mode of data collection

Face-to-face [f2f]

Research instrument

Two enumeration forms were used: a "short form" and a "long form". The "short form" was given to 80 percent of the families and comprised questions concerning basic demographic topics for each person in the family. The rest of families (20 percent) were given the long form.

Response rate

COVERAGE: 97.73%

Abstract

The main aim for the establishment census 2012 is to enumerate all of the economic establishments operating in Palestine in 2012, except for those establishments engaged in farming activities, and building a new updated a classified establishment register according to the geographical distribution, main economic activity according to international recommendations.

The goals for the Establishment Census could be summarized as follows: 1. Distribution of establishments by various economic activities. 2. Distribution of establishments by the Palestinian governorates. 3. The size of employment in various economic activities and its distribution by sex. 4. Distribution establishments in terms of economic organization, legal status, ownership and operation status. 5. The value of capital invested in establishments. 6. Distribution establishments in terms of registration status with the official authorities. 7. The rate of growth in the number of economic establishments.

Geographic coverage

The Establishment Census 2012 includes all of the establishments in Palestine, whether those of the government or international organizations and institutions, non-profit, and establishments engaged in economic activities in the markets or in factories and companies, or those that exercise an economic activity in houses and have the definition of an establishment, with the exception of those establishments engaged in the agriculture, forestry, fishing and animal husbandry

Analysis unit

Establishment

Universe

The establishment considered the statistical unit that the data collection was upon, which is an institution or part of it, which is located in one place and specializes mainly in one major activity (non Assistant) which will bring most of the added value, classified within the same activity (with probability of production of secondary activities) and for which data are available, allowing for calculating of operating surplus account, which provides data for both: workers, and expenses, production and revenue, and fixed assets. An establishment must provide the following requirements: 1.Participation in an economic activity, any establishment should provide good or service to the market. 2.The presence in a fixed place. 3.A holder of an establishment, whether an individual or a legal entity. 4.The presence of a single management of the establishment

Kind of data

Census/enumeration data [cen]

Sampling procedure

comprehensive census of all economic establishment in palestine

Mode of data collection

Face-to-face [f2f]

Research instrument

The establishment Census form consisted of two sections:

Part one: Identification data, which included basic information about the establishments, governorate, Locality, number of enumeration area, Building No. in the enumeration area, serial number of establishment in the enumeration area, establishment commercial name, name of holder or director, sex of the holder or director, phone number, location and description, including the name of the neighborhood and the street and the name of the building or the owner of the building, and the working status of the establishment.

Part two: data on operating establishments only, which include: (Description of the main economic activity, Ownership, Economic organization, Legal status, Establishment Year, Number of employees, Preparing of accounting records, Licensing and registration, No. workers, present value of capital, owner Identity No. or director of the of establishment).

Special form for Jerusalem Governorate area (J1) Due to the special situation in the Jerusalem governorate, specially J1 area (those parts of Jerusalem which were annexed by Israel in 1967) a short form for census questionnaire has been designed, which include the following questions: (Identification data for the establishment, working status, main economic activity, ownership of establishment, economic organization, establishment year, the number of employees in the establishment (paid, unpaid)).

Cleaning operations

The data processing stage includes editing, coding, data entry, reviewing lists and checking all previous operations of data entry for all enumeration areas. All procedures and instructions were conducted to check the consistency of the data and coding fields and ensure the entry of all enumeration areas and booklets and questionnaires, with their content of establishment data. As booklets and questionnaires required checking and moving from one operation site to another, a store was prepared for all the documents to be indexed and categorized and the store keeper controlled the flow of documents.

Coding manuals were prepared and examined beforehand, as well as the instructions for editing and coding procedures to check the consistency of the data and how to detect and correct errors. All editing and coding employees were selected from among the best fieldworkers who collected the data from establishments owners or manager. Training was conducted centrally to ensure uniform concepts and to eliminate disparities in fieldwork in all governorates. Editing, coding and testing the consistency of 100% of the questionnaires was conducted, in addition to desk reviewing, editing and coding (100%) in order to eliminate differences between individual editors and to discover and correct errors and circulate them daily.

Tests were held for all applicants for data entry and those who performed best were trained centrally in a uniform procedure of data entry. During the first three days, all date entered were deleted and re-entered again to correct errors and inform employees so as to avoid such errors in the future. Certain procedures were adopted to ensure correct data entry: in the first stage a unique separate file was prepared for each enumeration area that included identification data (to ensure coverage), the number of establishments and the total number of booklets to ensure that all booklets and all households had been entered. Upon data entry, a thorough examination of the identification data and the range of each digital key question was conducted so that the computer did not accept any figure outside this range. For example, the operation status, sex and all the pre-coded questions in the establishment questionnaire, and the type of building in the buildings questionnaire. The remaining questions were exposed to a comprehensive re-examination of the range of each question after data entry and the extraction of error lists resulting from data inconsistency.

After data entry, certain lists were extracted to ensure the coverage of all enumeration areas, and establishments, and to examine the internal consistency of the data of each unit. The procedures used were to extract error lists that must be corrected or questioned These lists were submitted to the best reviewers under full supervision of the technical operations in the census directorate.

Specific programs previously prepared were used to detect errors according to the following procedures: 1. An instruction manual was prepared for desk editing and procedures for the establishments' questionnaire. A set of desk editing instructions were printed and the procedures for the questionnaire containing tests designed to ensure the coverage of data entry, to detect inconsistencies or to detect abnormal and rare cases. These were reviewed and printed with a name and number given to every error in the manual. 2. A list was extracted for each enumeration area, including the identification data of each establishment message (type of check) and the number printed in the manual. The auditor could then recognize the message name and type of error, location and procedures of editing and audit procedures patch, which consists of several checks on several stages. 3. Lists were submitted to the reviewers to return to the original booklets. If the error was caused by data entry, it would be corrected on the list. If the error was due to fieldwork, all associated questions should be considered for correction. For example, if the operation status of the establishment was closed, it must be no answers on the questions after it. The first check would be conducted through manual editing, then extracting the electronic lists after data entry for such types of tests, then they would be corrected manually on the original booklets and data re-entered correctly. As for the coverage test, there is a key reference that contains all enumeration areas and shows the number of booklets and establishments in the enumeration area to be entered on the computer. At this point, if there was a variation between the number of booklets and establishments actually entered and the total number of establishments in the file of each area, an error message appears to request correction. Through this method, we ensured that 100% of the establishments were entered.

All lists for the enumeration areas were extracted in this way and all kinds of tests. 1. Amended lists were sent back to data entry to be entered and corrected and a copy of the daily entered data was kept in several different places. 2. Previous stages were conducted twice or more until the data of each enumeration area became clean. 3. All files were compiled for enumeration areas for each locality and governorate. Then, all tables and any additional tests were conducted to test the data before the final tabulation in order to correct errors according to the aforementioned procedures.

Sampling error estimates

-

Data appraisal

There are two types of error that can occur: statistical errors and

The American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs), which are statistical measures that show the relative amount of sampling error associated with an estimate, are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2009 - 2013 data is the census tract - a small statistical area within a county, which is delineated every 10 years prior to the decennial census.This is a MD iMAP hosted service. Find more information on https://imap.maryland.gov.Feature Service Link: https://archive.geodata.md.gov/imap/rest/services/Demographics/MD_ArchivedAmericanCommunitySurvey/FeatureServer/2

This statistic shows the forms of yogurt or smoothies eaten most often in the United States from 2012 to 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 116.58 million Americans consumed spoonable (eat with a spoon) yogurt or smoothies in 2020.

The units of geography used for the 2010 Census maps displayed here are the Census tracts. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. Census tract boundaries generally follow visible and identifiable features. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. The data collected on the short form survey are general demographic characteristics such as age, race, ethnicity, household relationship, housing vacancy and tenure (owner/renter).This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://geodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer/0

Abstract

Objectives:

The objectives could be summarized as follows: a. Update the establishment/enterprise register for different uses, i.e. as a sampling frame for economic surveys. b. Identifying the number of operating establishments and number of persons engaged in the different economic activities by geographical location. c. Identifying the most prominent characteristics of all operating establishments such as legal status, organization, ownership and others.

Geographic coverage

The Establishments Census 1997 includes all economic establishments in Palestine

Analysis unit

Establishment

Universe

all economic establishments in Palestine

Kind of data

Census/enumeration data [cen]

Sampling procedure

comprehensive census of all economic establishment in palestine (not applicable(

Sampling deviation

comprehensive census of all economic establishment in palestine (not applicable(

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire used includes several basic variables appropriate to census objectives. such variables are explained in relevant sectors of census manuals. These manuals also fully explain the methods of data collection. The design of the questionnaire was made in consideration of both the plan and cost of the Population, Housing and Establishment census. The questionnaire contains the following:

· Serial number of establishment · Number of numeration area · Number of building in the numeration area · Number of the establishment in the numeration area · Address · Commercial name · Phone · Owner or manager name
· Establishment Status
· Ownership Type
· profit or non Profit organization · Economic organization · Legal status
· No of employees
· No of employees/Male
· No of employees/Female

Cleaning operations

Stages from planning to data collection were fully integrated with the other components of the PHC. Post data collection activities (i.e. data processing and tabulation) for the Establishment component were carried out separately. In general stages consist of:

5.1 Preparation stage: Activities of this stage include developing the questionnaire, manual, reporting forms, tabulation plan, editing and coding rules and work plan in terms of all required resources and the time-table. This stage also encompasses the pilot census where all documents and plans are tested. 5.2 Implementation stage: Includes: Fieldwork operations: The PHC fieldwork team allocated for the second phase, as mentioned above, carried out the data collection for the Establishment Census. This team included about 1,000 persons. Data processing and tabulation: this phase included: Pre-data entry editing Coding Data entry Online checks Post-data entry editing Tabulation Table quality control Drafting report and publication

Response rate

comprehensive census of all economic establishment in palestine (not applicable(

Sampling error estimates

not applicable its census

This is a MD iMAP hosted service. Find more information on http://imap.maryland.gov. The American Community Survey (ACS) is a nationwide - continuous survey designed to provide communities with reliable and timely demographic - housing - social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs) - which are statistical measures that show the relative amount of sampling error associated with an estimate - are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2009 - 2013 data is the census tract - a small statistical area within a county - which is delineated every 10 years prior to the decennial census. Map Service Link: http://archive.geodata.md.gov/imap/rest/services/ Demographics/MD_ArchivedAmericanCommunitySurvey/MapServer/2 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

The ACS-ED Maps tool identifies conditions of school-age children in school districts based on data from the U.S. Census Bureau’s American Community Survey Education Tabulation (ACS-ED) 2013-17.The American Community Survey – Education Tabulation (ACS-ED) is an annual, nationwide survey designed to provide communities with reliable and timely demographic, social, economic, and housing data. The U.S. Census Bureau implemented the ACS in 2005 as a replacement for the decennial census long form, and NCES collaborates with the U.S. Census Bureau to create a variety of custom ACS data files that describe the condition of school-age children in the U.S., states, and school districts. The custom NCES files are updated annually and based on ACS five-year period estimates.Population Groups:The ACS Children's tabulation provides characteristics of school-age children with separate iterations based on enrollment and school type. Iterations include: Total Children; Grade-relevant Children; Grade-relevant Children - Enrolled; and Grade-relevant Children - Enrolled Public. Learn more.The ACS Total Population tabulation includes all persons living in households or group quarters. The total population files offered by NCES include estimates for the nation, states, and school districts, ACS estimates for additional geographic areas are available from the U.S. Census Bureau's American FactFinder System. Learn more.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No (dwellings in original sample are interpreted as households in IPUMS) - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Structurally independent living quarters, consisting of one or more rooms with a private entrance, serving up to three families. - Group quarters: Group living together under relations of administrative subordination; group of six or more persons not related by kinship; or a dwelling with more than 3 families.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Instituto Brasileiro de Geografia e Estatística

SAMPLE UNIT: Household (called "dwelling" in original sample)

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 4,953,759

Mode of data collection

Face-to-face [f2f]

Research instrument

Long and short enumeration forms. The short form contains general information about the characteristics of the dwelling and each of persons in the dwelling. The long form contains general and more specific information about the characteristics of the dwelling, families, and each of the people in the dwellings and was applied to a 25% sample of the population.

Response rate

COVERAGE: No official estimates, UNDERCOUNT: No official estimates

Abstract

Six agricultural censuses have been conducted in Italy in the years 1961, 1970, 1982, 1990, 2000 and the latest, to which data here refer, in 2010.

Its objective is:

a) to provide a statistical picture on the structure of the agricultural and livestock system at national, regional and local level.

b) to fulfil the Regulation (EC) n. 1166/2008 of the European Parliament and of the Council of 19 November 2008 on farm structure (FSS) and the survey on agricultural production methods (SAPM) and the Council Regulation (EEC) No 357/79 of 5 February 1979 on statistical surveys of areas under vines.

c) To update and validate the statistical register of the agricultural holdings built up by Istat through the integration of the administrative sources.

The Agricultural Census cover all agricultural holdings whoever is its management, with Utilized Agricultural Area (UAA) or livestock equal or higher than minimum thresholds stated by Istat.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit is the agricultural holding, defined as a single unit, both technically and economically, which has a single management and which undertakes the agricultural activities listed in Annex I to the European Parliament and Council Regulation (EC) No. 1166/2008 within the economic territory of the EU, as either its primary or secondary activity. Specific actions have been implemented to include all common lands with UAA2 in the AC 2010.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Frame: The pre-census list of agricultural holdings was established based on the integration of administrative and statistical sources that contain information concerning the target population. The AC was conducted using complete enumeration.

Mode of data collection

Face-to-face [f2f]

Research instrument

There was one comprehensive census questionnaire, available either in print form or as and Internet-based electronic version that could be completed online. It was available in four languages (Italian, German, English and Slovenian). The questionnaire was used to collect both farm structure characteristics as well as items related to agricultural production methods. The questionnaire included all 16 core items recommended in the WCA 2010.

Questionnaire sections:

• General company news
• Information for companies with land
• Information for farms with livestock
• Location of land and farms
• Work and related activities (agricultural year 2009 - 2010)
• Other information (agricultural year 2009 - 2010)

Cleaning operations

1. DATA PROCESSING AND ARCHIVING Manual data entry was used (for paper questionnaires) along with direct data capture (when CAWI was used). Non-sampling errors were identified and treated by an Editing and Imputation System. For detecting outlier values, a special procedure based on the robust technique of Forward Search was implemented, in partnership with the University of Parma and centrally applied by ISTAT. The imputation process used was a combination of the following methodologies: (i) deductive imputation, if the values to impute are uniquely determined by the values assumed by other variables; (ii) rule-based imputation (based on deterministic "if then" rules); (iii) nearest neighbour imputation; (iv) model-based imputation (preferred for the imputation of continuous variables); and (v) interactive imputation. Administrative sources were used for the preparation of the pre-census list, for data control and correction.

2. CENSUS DATA QUALITY To evaluate the quality of the AC 2010, Istat implemented two PESs ("post-census surveys"): a Coverage Survey (CS) and a Re-Interview Survey (RIS). The CS was designed to obtain reliable estimates of under- or overcount, using another independent list of units existing in a sample of cadastral maps. The RS was carried out through a re-interview of a sample of agricultural holdings already interviewed in the AC to estimate response error due to respondents and/or enumerators. The survey was carried out from May 2011 to January 2012 on a sample of approximately 50 000 holdings, selected with one-stage stratified sample from the census frame. The survey was conducted using CATI.

Sampling error estimates

The non-sampling errors has been identified and treated by an Editing and Imputation System (E&IS), preserving as much as possible the collected information. The E&I activities could be grouped in three main stages. The first stage refers to the checks performed at the data gathering phase. The second stage concerns the activities carried out in order to provide the provisional figures. The last stage relates to the procedures aiming to release the final data.

Data appraisal

Preliminary results were disseminated in July 2011 through a press release and 23 tables were made available to users on the Istat website. The final results were released in July 2012. The main dissemination method was the Internet.

The papers relate chiefly to the printing of forms for the 1856 Census. Also included are copies of instructions for the taking of the Census in 1851 and in 1856.

There is a printed circular of suggestions from the Colonial Office on the method of taking a census, dated 1848, and a bundle of memos from the Government Printer concerning the despatch of forms to various districts.

(4/6846.2). 1 bundle.

Note:

This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

Abstract

There is a long history to the agricultural census in the Netherlands. From 1934 onwards a census has been carried out (almost) every year. In recent years it is no longer purely a statistical project, but serves several purposes: on the one hand production of statistics by Statistics Netherlands and creating a frame for sampling, on the other hand providing data on individual holdings for administrative purposes by the Ministry of Economic Affairs, Agriculture and Innovation (the Ministry). Since the Ministry and Statistics Netherlands have a common interest in the census, it is held as a joint effort. In 1990, it was the last time special meeting days were organised to assess the data from the farmers. On these meeting days, farmers and enumerators jointly filled in the questionnaire manually. In the period 1991 – 1995, these sessions still took place, but the manual procedure was gradually replaced by filling in the information in a computer file. In 1996, the farmer could make a choice between coming to a special meeting place or filling in the survey form himself and returning it by postal mail. From 1997 on, a complete census was organised by postal mail every year. The year 2003 was a pilot year in which respondents had the opportunity to supply the census information through an internet application. In recent years the information is predominantly supplied via the internet. Since the statistical year 2002 the questionnaire of the agricultural census is combined with the application for animal, crop and arable land subsidies (in 2006 also for the single payment scheme). In 2007 data collection for the enforcement of the manure law is also combined in this questionnaire. This is done for efficiency reasons, both for farmers, and for administration and processing of data.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as a single unit, both technically and economically, which has a single management and which undertakes agricultural activities listed in Annex Ito the European Parliament and Council Regulation (EC) No. 1166/2008 within the economic territory of the EU, either as its primary or secondary activity.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Frame Statistics Netherlands has a business register of all industrial and non-industrial commercial establishments, but the agricultural holdings are not yet fully covered in this register. The agricultural census therefore relies on the administrative farm register (AFR) of the Ministry held by NSIR, an executive service of the Ministry. By law farmers have to register with NSIR. The AFR contains names, addresses and a few other characteristics of holders or holdings and a unique registration number. With the census information of several years Statistics Netherlands has built up a statistical farm register (SFR). Relevant characteristics from the AFR (a.o. identification number, addresses, legal status) are also stored in the SFR. Changes in addresses are entered into the AFR throughout the year, changes in the SFR of course only once a year. The SFR provides a magnificent basis for stratification and efficient sampling of subsequent agricultural statistics. An annual census may seem expensive (even when only half of the cost is looked upon as expenses for statistics). But the excellent quality of the sample frame allows for relative small samples in related agricultural statistics and thus reduction of costs.

Mode of data collection

Computer Assisted Web Interview (CAWI)

Research instrument

One questionnaire was used, integrating both the 2010 AC and the SAPM, and presented to respondents as a single statistical inquiry. The questionnaire covered all 16 core items recommended in the WCA 2010.

Questionnaire:

1 Work and education 2 Number of animals and housing 3 Horticulture under glass 4 Mushrooms, bulb growing, chicory growing 5 Crops on open land and land use 6 Agricultural land area 7 Subsidies 8 Farm data 9 Livestock manure 10 Excavation notification (WION) 11 Signature

Cleaning operations

a. Data collection and data entry About 85% of the questionnaires was filled in and returned using the web application, which already contained a lotof c hecks and validations. Paper forms were digitized by a data-entry firm and processed by NSIR in the same way as the online questionnaires. There were several quality controls to ensure correct digitization.

b. Data processing, estimation and analysis Data processing, estimation and analysis were performed in two successive stages:

1. Pre-processing at NSIR After data collection and data entry the input data go through an extensive error control phase. In this phase checks are made on missing values, valid values, unlikely values, range checks, checks of correlation in the data, checks of totals and so on. When necessary additional information is collected from the farmers by phone. Data that is checked and accepted by NSIR is forwarded to Statistics Netherlands.

2. Processing at Statistics Netherlands Processing at Statistics Netherlands involves additional error control, enrichment with additional information, such as total SO and typology, imputation for non-response and analysis. Analyses are made at several levels of aggregation and comprise comparison with previous results and agricultural data from other sources.

Data appraisal

Checking the information in the questionnaires took place using a special control programme. Data were checked for hard and soft errors. Hard errors are non-valid values. Soft errors are unlikely values. If necessary, the checking personnel contacted the respondent to correct for errors. Approximately 85 percent of the questionnaires were completed online. The online questionnaire application contained extensive interactive controls and edits.

Dissemination: Dissemination is done via the Statline database, which is available on the Internet (www.cbs.nl ). In this database, Internet users may select their own indicators and information topics. Short publications on specific subjects are presented in the form of newspaper or Internet articles. Safe access to census microdata is also provided.

Illawarra (4/1243A-C). 3 vols.

These records comprise Form A - Householders Returns and Form B - Collectors' Affidavits.
Form A records county, parish, town or district; name of householder, employer of servants, or person in charge; place of residence and street if in a town. Then follows a series of questions relating to the proprietor of the house, the substance the house was built of, the people residing in the house and how many of them were free.
On the other side of the form is a table headed "Numerical return showing the age, sex, religion, occupation, condition and trade and calling, of persons in the said House or Establishment".

Form B accompanies Form A. It is an affidavit form signed by the collector that the numbers taken are a true statement of the number and quality of the persons residing in the district. They showing running numbers covered by the returns with which they are filed. They are signed by the collector, the place and date are given and the signature of the Justice of the Peace or Police Magistrate for the area.

Port Phillip (4/1244A-C; microfilm copy SR Reels 1419 and 2509). 3 vols.

This form records on a single sheet the information noted on Forms A and B described above.

Note:
This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

A census is held every ten years in the Netherlands. Nowadays only already existing sources (registers and surveys) are being used. Since 1971 in the Netherlands there are no longer Census questionnaires for the Population and Housing Census.