In 2021, the average size of households in Utah was 2.99 people, the largest of any state. Hawaii, California, Idaho, and Texas rounded out the top five states for largest household size in that year. Nationwide, the average household size was 2.54 people.

This dataset shows the Principal statistics of medical laboratories by state, 2015Source: Department of Statistics Malaysia

The Comprehensive Annual Financial Reports are presented in three main sections; the Introductory Section, the Financial Section, and the Statistical Section. The Introductory Section includes a financial overview, discussion of Iowa's economy and an organizational chart for State government. The Financial Section includes the state auditor's report, management's discussion and analysis, audited basic financial statements and notes thereto, and the underlying combining and individual fund financial statements and supporting schedules. The Statistical Section sets forth selected unaudited economic, financial trend and demographic information for the state on a multi-year basis. Reports for multiple fiscal years are available.

About this dataset

Context

The dataset tabulates the population of State College by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of State College across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 53.83% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the State College is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of State College 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 State College Population by Race & Ethnicity. You can refer the same here

United States Unemployment Rate: Age 25 to 54 data was reported at 3.000 % in Oct 2018. This records an increase from the previous number of 2.900 % for Sep 2018. United States Unemployment Rate: Age 25 to 54 data is updated monthly, averaging 4.400 % from Jan 1948 (Median) to Oct 2018, with 850 observations. The data reached an all-time high of 9.700 % in Jan 1983 and a record low of 1.800 % in Aug 1953. United States Unemployment Rate: Age 25 to 54 data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G018: Current Population Survey: Unemployment Rate.

This excel contains results from the 2017 State of Narragansett Bay and Its Watershed Technical Report (nbep.org), Chapter 4: "Population." The methods for analyzing population were developed by the US Environmental Protection Agency ORD Atlantic Coastal Environmental Sciences Division in collaboration with the Narragansett Bay Estuary Program and other partners. Population rasters were generated using the USGS dasymetric mapping tool (see http://geography.wr.usgs.gov/science/dasymetric/index.htm) which uses land use data to distribute population data more accurately than simply within a census mapping unit. The 1990, 2000, and 2010 10m cell population density rasters were produced using Rhode Island state land use data, Massachusetts state land use, Connecticut NLCD land use data, and U.S. Census data. To generate a population estimate (number of persons) for any given area within the boundaries of this raster, NBEP used the the Zonal Statistics as Table tool to sum the 10m cell density values within a given zone dataset (e.g., watershed polygon layer). Results presented include population estimates (1990, 2000, 2010) as well as calculation of percent change (1990-2000;2000-2010;1990-2010).

State, 2016 –2020; County, 2020. The report includes both state and county level water fluoridation data generated from the Water Fluoridation Reporting System (WFRS). State level statistics include data from the biennial report originally published at https://www.cdc.gov/fluoridation/statistics/reference_stats.htm. State and county data include percentage of people, number of people, and number of water systems receiving fluoridated water. County level data is not displayed for all states. Participation in sharing county level data is voluntary and state programs determine if data will be shown.

As of December 31, 111............................

This dataset contains information on structures that are owned by the State of Connecticut.

This inventory is currently maintained by the Office of Policy and Management (OPM) and information is self-reported by those State agencies that have custody and control over State owned buildings.

For additional information about this data, please contact the agency which is listed as owning the property. This data is updated each March.

Colorado Department of Public Health and Environment COVID19 Daily State Statistics contains published state-level data and statistics on the following indicators: number of cases, people tested, deaths among cases, deaths due to COVID-19 (death certificate), rate of COVID-19 infection per 100,000 persons, COVID-19 hospitalizations, counties with cases, and number of outbreaks. This dataset represents a cumulative repository of daily published data.

United States Unemployment Rate: North Dakota data was reported at 2.900 % in Jun 2018. This records an increase from the previous number of 2.200 % for May 2018. United States Unemployment Rate: North Dakota data is updated monthly, averaging 3.700 % from Jan 1976 (Median) to Jun 2018, with 510 observations. The data reached an all-time high of 7.400 % in Mar 1983 and a record low of 1.600 % in Oct 1997. United States Unemployment Rate: North Dakota data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G057: Unemployment Rate: By State.

Graph and download economic data for All Employees: Government in Montana (MTGOVTN) from Jan 1990 to Apr 2025 about MT, government, employment, and USA.

This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: April 2025 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: May 28th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

About this dataset

Context

The dataset tabulates the State College 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 State College. The dataset can be utilized to understand the population distribution of State College by age. For example, using this dataset, we can identify the largest age group in State College.

Key observations

The largest age group in State College, PA was for the group of age 20-24 years with a population of 15,950 (39.53%), according to the 2021 American Community Survey. At the same time, the smallest age group in State College, PA was the 80-84 years with a population of 316 (0.78%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 State College is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of State College 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 State College Population by Age. You can refer the same here

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

In 2022, California had 10,952 drug overdose deaths. Opioids are the main driver of overdose deaths. This statistic presents the number of drug overdose deaths in the U.S. in 2022, by state.

The dataset contains Year and State wise Area, Production and Yield of Foodgrains - Rice

Note: 1. All India data are inclusive of all States and Union Territories.

This data contains general government sector operating expenses, sourced from the Australian Bureau of Statistics historical data and the Department of Treasury and Finance, categorised by ‘government purpose classification’ (GPC) and ‘classification of the functions of government’ (COFOG).\r \r The Australian system of Government Finance Statistics (GFS) was revised by the Australian Bureau of Statistics, with the release of the Australian System of Government Finance Statistics: Concepts, Sources and Methods 2015 Cat. No. 5514.0.\r \r Implementation of the updated GFS manual has resulted in the COFOG framework replacing the former GPC framework, with effect from the 2018-19 financial year for financial reporting under AASB 1049.\r \r The underlying data from 1961-62 to 1997-98 represents a conversion from the original cash series to an accruals basis by estimating depreciation and superannuation expenses based on statistical modelling.\r \r Although the conversion provides a basis for comparison with total expenses in the current series of accrual GFS information from 1998 (in the attached table), the estimated accrued expense items have not been apportioned to individual purpose classifications.\r \r The absence of these splits between functional classifications in the attached table data therefore represents a break in the series and it is not possible to compare individual purpose categories with those in other tables.\r \r Similarly, the transition from GPC to COFOG represents an additional break in the series and comparability between the two frameworks will not be possible.\r \r The key reporting changes from GPC to COFOG are as follows:\r \r - the number of categories has reduced from 12 under GPC to 10 under COFOG; \r - the fuel and energy, agriculture, forestry, fishing and hunting categories have been abolished and are now part of the new economic affairs category. The majority of the outputs in other economic affairs are also included in this new category;\r - public debt transactions have moved from the other purposes category (i.e. primarily interest expense on borrowings) to general public services category;\r - a new environmental protection category was created to include functions such as waste management, water waste management, pollution and production of biodiversity and landscape, which were previously classified under housing and community amenities category, as well as national and state parks functions from the recreation and culture category; and\r - housing functions such as housing assistance and housing concessions are now part of the social protection category

Number of life insurance policies for each administered life insurance program listed by state. Data is current as of 4-30-11. All programs are closed to new issues except for Service-Disabled Veterans' Insurance and Veterans' Mortgage Life Insurance. United States Government Life Insurance was issued to WWI military personnel and Veterans. National Service Life Insurance was established to meet the needs of WWII military personnel and Veterans. Veterans' Special Life Insurance was issued to Korean War-era Veterans. Veterans' Reopened Insurance provides coverage to certain classes of disabled Veterans from WWII and the Korean conflict who had dropped their government life insurance coverage. Service-Disabled Veterans' Insurance was established in 1951 and is available to Veterans with service-connected disabilities. Veterans' Mortgage Life Insurance was established in 1971 to provide mortgage protection life insurance to severely disabled Veterans who have received grants for the purchase of specially-adapted housing.