Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

Monthly data on federally administered Supplemental Security Income payments.

United States AHE: sa: PW: PB: Packaging & Labeling Services data was reported at 20.630 USD in Nov 2022. This records an increase from the previous number of 20.430 USD for Oct 2022. United States AHE: sa: PW: PB: Packaging & Labeling Services data is updated monthly, averaging 13.020 USD from Jan 1990 (Median) to Nov 2022, with 395 observations. The data reached an all-time high of 20.630 USD in Nov 2022 and a record low of 7.360 USD in Jan 1990. United States AHE: sa: PW: PB: Packaging & Labeling Services data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G076: Current Employment Statistics: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

110 years of current demographic data provided by this collection

United States AHE: PW: Information: Periodical Publishers data was reported at 32.270 USD in Nov 2022. This records an increase from the previous number of 31.420 USD for Oct 2022. United States AHE: PW: Information: Periodical Publishers data is updated monthly, averaging 27.430 USD from Jan 2003 (Median) to Nov 2022, with 239 observations. The data reached an all-time high of 32.710 USD in Oct 2020 and a record low of 18.150 USD in Jan 2003. United States AHE: PW: Information: Periodical Publishers data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G075: Current Employment Statistics: Average Hourly Earnings: Production Workers.

The monthly resident population statistics by gender and age for each township and city in Changhua County.

DO NOT EDIT THIS DATASET. This dataset, which is automatically updated contains Bureau of Labor Statistics data. This dataset is updated by a Socrata process; please contact support@socrata.com if you encounter any questions or issues.

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, and migration from the March Annual Demographic Supplement and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.

United States Diffusion Index: sa: Mfg: 3 Months Span data was reported at 67.100 Unit in Oct 2018. This records an increase from the previous number of 63.200 Unit for Sep 2018. United States Diffusion Index: sa: Mfg: 3 Months Span data is updated monthly, averaging 49.000 Unit from Jan 1991 (Median) to Oct 2018, with 334 observations. The data reached an all-time high of 82.200 Unit in Nov 1997 and a record low of 2.600 Unit in Mar 2009. United States Diffusion Index: sa: Mfg: 3 Months Span 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.G041: Current Employment Statistics Survey: Diffusion Index.

CD617 - Population Usually Resident and Present in the State. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Population Usually Resident and Present in the State...

Selected variables from the most recent ACS Community Survey (Released 2023) aggregated by Community Area. Additional years will be added as they become available. The underlying algorithm to create the dataset calculates the % of a census tract that falls within the boundaries of a given community area. Given that census tracts and community area boundaries are not aligned, these figures should be considered an estimate. Total population in this dataset: 2,647,621 Total Chicago Population Per ACS 2023: 2,664,452 % Difference: -0.632% There are different approaches in common use for displaying Hispanic or Latino population counts. In this dataset, following the approach taken by the Census Bureau, a person who identifies as Hispanic or Latino will also be counted in the race category with which they identify. However, again following the Census Bureau data, there is also a column for White Not Hispanic or Latino. Code can be found here: https://github.com/Chicago/5-Year-ACS-Survey-Data Community Area Shapefile: https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Community-Areas-current-/cauq-8yn6 Census Area Python Package Documentation: https://census-area.readthedocs.io/en/latest/index.html

This data presents provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National provisional counts include deaths occurring within the 50 states and the District of Columbia as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts. Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts. Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made. Provisional data presented will be updated on a monthly basis as additional records are received. For more information please visit: https://www.cdc.gov/nchs/nvss/vsrr/drug-overdose-data.htm

This statistic displays the result of a survey where eHealth professionals from Germany in 2021 were asked to evaluate the biggest eHealth priorities for healthcare providers. In this year, 92 percent of respondents believed that IT security and data privacy was the highest priority, while 73 percent believed system usability and user experience was a priority.

This dataset presents statistics on: the number of establishments; sales, value of shipments, or revenue; annual payroll; and number of employees whose NAICS classification has changed between the current and the previous economic censuses. Data are shown for 6-digit previous economic census NAICS industries and their 8-digit current economic census NAICS components for the U.S. Includes only establishments of firms with paid employees.

About this dataset

Context

The dataset tabulates the population of Jasper town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Jasper town. The dataset can be utilized to understand the population distribution of Jasper town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Jasper town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Jasper town.

Key observations

Largest age group (population): Male # 55-59 years (77) | Female # 0-4 years (81). 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.

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

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.

Variables / Data Columns

• Age Group: This column displays the age group for the Jasper town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Jasper town is shown in the following column.
• Population (Female): The female population in the Jasper town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Jasper town for each age group.

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 Jasper town Population by Gender. You can refer the same here

United States Avg Weekly Earnings: IF: Telecommunications Reseller data was reported at 1,213.730 USD in May 2018. This records a decrease from the previous number of 1,285.570 USD for Apr 2018. United States Avg Weekly Earnings: IF: Telecommunications Reseller data is updated monthly, averaging 1,132.910 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 1,375.530 USD in Oct 2011 and a record low of 973.530 USD in Apr 2009. United States Avg Weekly Earnings: IF: Telecommunications Reseller 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.G032: Current Employment Statistics Survey: Average Weekly and Hourly Earnings.

FluWatch is Canada's national surveillance system that monitors the spread of flu and flu-like illnesses on an on-going basis. Activity Level surveillance is a component of FluWatch that provides an overall assessment of the intensity and geographical spread of laboratory-confirmed influenza cases, influenza-like-illness (ILI) and reported outbreaks for a given surveillance region. Activity Levels are assigned and reported by Provincial and Territorial Ministries of Health. A surveillance region can be classified under one of the four following categories: no activity, sporadic, localized or widespread. For a description of the categories, see the data dictionary resource. For more information on flu activity in Canada, see the FluWatch report. (https://www.canada.ca/en/public-health/services/diseases/flu-influenza/influenza-surveillance/weekly-influenza-reports.html) Note: The reported activity levels are a reflection of the surveillance data available to FluWatch at the time of production. Delays in reporting of data may cause data to change retrospectively.

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 50.68% of total population being female. 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.

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 Raleigh is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Raleigh 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 Raleigh Population by Gender. You can refer the same here

The High Current Shunt Resistor market plays a crucial role in various industries, including automotive, telecommunications, and renewable energy, by providing precise current measurement and monitoring solutions. These resistors are engineered to handle significant currents while maintaining accuracy and reliabilit

How did the data collection work?
The goal of the study is to compare the performance on data analysis tasks when using the data analysis tool eyenalyzer or others. Hence, participants are randomly assigned to one of two groups (i.e., with and without eyenalyzer). All participants work on the same six data analysis tasks - according to their group assignment either with the tool eyenalyzer or with any other tool apart from it. After a maximum of two hours, the participants hand in their solutions to the tasks as well as a self-report of the time taken to complete each task (in minutes), the tooling used for each task (as list), and the estimated difficulty of each task (on a 7-point Likert scale). Finally, they fill out a questionnaire about their demographic data (i.e. age, gender, and previous experience). The submitted solutions are later graded in terms of correctness. Further details on the procedure can be found in this conference paper.

What data is provided?
In this repository you can find both the data obtained from 20 participants (i.e., file data.xlsx) and a german replication package (i.e., folder material.zip).

1. The data file data.xlsx comprises 13 columns and 120 rows. Each row represents one combination of participant and task. The columns are:
   • participant the current participant as a unique identifier from {P01, ..., P20}
   • independent_variable the group assignment of the participant as one of {eyenalyzer, others}
   • task the current task as one of {T1, ..., T6}
   • score the grading of the current task for the current participant as one of {not completed, wrong, borderline, acceptable, correct}
   • time time used by the current participant for the current task in minutes
   • difficulty difficulty estimate of the current participant for the current task as one of {very difficult, difficult, rather difficult, indecisive, rather easy, easy, very easy}
   • tools_used listing of tooling used for the current task if the current participant belongs to the group without eyenalyzer
   • age age of the current participant in years
   • gender gender of the current participant as one of {male, female}
   • experience_programming previous experience of the current participant in programming as one of {none, little, indecisive, some, much}
   • experience_data_science previous experience of the current participant in data science as one of {none, little, indecisive, some, much}
   • experience_experimental_research previous experience of the current participant in experimental research as one of {none, little, indecisive, some, much}
   • experience_statistics previous experience of the current participant in statistics as one of {none, little, indecisive, some, much}
2. The replication folder material.zip comprises three subfolders with the following material:
   • group_with_eyenalyzer/primer.pdf information material on statistics provided to the group with eyenalyzer
   • group_with_eyenalyzer/tasks.pdf the instructions provided to the group with eyenalyzer
   • group_without_eyenalyzer/primer.pdf information material on statistics provided to the group without eyenalyzer
   • group_without_eyenalyzer/tasks.pdf the instructions provided to the group without eyenalyzer
   • both_groups/data/ a directory containing the 4 data files needed to complete the tasks (based on the data from this repository)
   • both_groups/questionnaire.pdf a transcription of the demographic questionnaire

Do you have further questions?
For more information, please feel free to contact