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.

BackgroundIn medical practice, clinically unexpected measurements might be quite properly handled by the remeasurement, removal, or reclassification of patients. If these habits are not prevented during clinical research, how much of each is needed to sway an entire study?Methods and ResultsBelieving there is a difference between groups, a well-intentioned clinician researcher addresses unexpected values. We tested how much removal, remeasurement, or reclassification of patients would be needed in most cases to turn an otherwise-neutral study positive. Remeasurement of 19 patients out of 200 per group was required to make most studies positive. Removal was more powerful: just 9 out of 200 was enough. Reclassification was most powerful, with 5 out of 200 enough. The larger the study, the smaller the proportion of patients needing to be manipulated to make the study positive: the percentages needed to be remeasured, removed, or reclassified fell from 45%, 20%, and 10% respectively for a 20 patient-per-group study, to 4%, 2%, and 1% for an 800 patient-per-group study. Dot-plots, but not bar-charts, make the perhaps-inadvertent manipulations visible. Detection is possible using statistical methods such as the Tadpole test.ConclusionsBehaviours necessary for clinical practice are destructive to clinical research. Even small amounts of selective remeasurement, removal, or reclassification can produce false positive results. Size matters: larger studies are proportionately more vulnerable. If observational studies permit selective unblinded enrolment, malleable classification, or selective remeasurement, then results are not credible. Clinical research is very vulnerable to “remeasurement, removal, and reclassification”, the 3 evil R's.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 149 zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than 394 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just two percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of 19.2 percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached 6.7 zettabytes.

Current Employment Statistics - June 2024

Analysis of ‘CT Department of Labor, Office of Research - Current Employment Statistics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/9b34e508-4cb9-4944-a75d-f622747113a4 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Current Employment Statistics - Sept. 2021

--- Original source retains full ownership of the source dataset ---

Compositional data, which is data consisting of fractions or probabilities, is common in many fields including ecology, economics, physical science and political science. If these data would otherwise be normally distributed, their spread can be conveniently represented by a multivariate normal distribution truncated to the non-negative space under a unit simplex. Here this distribution is called the simplex-truncated multivariate normal distribution. For calculations on truncated distributions, it is often useful to obtain rapid estimates of their integral, mean and covariance; these quantities characterising the truncated distribution will generally possess different values to the corresponding non-truncated distribution.

In the paper Adams, Matthew (2022) Integral, mean and covariance of the simplex-truncated multivariate normal distribution. PLoS One, 17(7), Article number: e0272014. https://eprints.qut.edu.au/233964/, three different approaches that can estimate the integral, mean and covariance of any simplex-truncated multivariate normal distribution are described and compared. These three approaches are (1) naive rejection sampling, (2) a method described by Gessner et al. that unifies subset simulation and the Holmes-Diaconis-Ross algorithm with an analytical version of elliptical slice sampling, and (3) a semi-analytical method that expresses the integral, mean and covariance in terms of integrals of hyperrectangularly-truncated multivariate normal distributions, the latter of which are readily computed in modern mathematical and statistical packages. Strong agreement is demonstrated between all three approaches, but the most computationally efficient approach depends strongly both on implementation details and the dimension of the simplex-truncated multivariate normal distribution.

This dataset consists of all code and results for the associated article.

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Note that the pre-registration can be found here: https://osf.io/xs5wf.

United States AHE: sa: PW: PB: Scientific Research & Development Services data was reported at 58.190 USD in Dec 2024. This records an increase from the previous number of 57.230 USD for Nov 2024. United States AHE: sa: PW: PB: Scientific Research & Development Services data is updated monthly, averaging 31.150 USD from Jan 1990 (Median) to Dec 2024, with 420 observations. The data reached an all-time high of 58.190 USD in Dec 2024 and a record low of 15.440 USD in Feb 1990. United States AHE: sa: PW: PB: Scientific Research & Development 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.G071: Current Employment Statistics Survey: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

The Travel Technologies market has evolved significantly over the years, playing a critical role in shaping the way people experience travel today. With a global market size that reached approximately $8 billion in 2022, the sector has witnessed unprecedented growth, driven by the increasing demand for efficient tra

An orientation on data and statistics.. Visit https://dataone.org/datasets/sha256%3A63927513ff7b8de7118f0a7683e6c00092f94016062371c66ef8873d78f645a2 for complete metadata about this dataset.

The 2024 fiscal year marked a slight increase in Oracle Corporation’s research and development spending, the yearly total climbing to 8.9 billion U.S. dollars from the 6.5 figure recorded in 2021. Following years of dramatically expanding R&D budgets, the company seems to have slowed R&D budget expansion and stabilized the figure at around seven to eight billion. Oracle Founded in 1977, Oracle is a tech company primarily focused on relational database technology. Today, Oracle ranks among the largest companies in the world in terms of market value and serves as the world’s most popular database management system provider. In addition to its investment into R&D, the company is also known for its use of acquisitions to promote growth, with high profile purchases including Sun Microsystems, PeopleSoft, and NetSuite. Research and Development spending As one of the largest software and computer services companies, Oracle is also among the biggest R&D spenders. However, many of the company’s peers tend to spend far more on R&D, with Alphabet, Microsoft, and Facebook all spending well over ten billion euros in 2019/20.

United States Avg Weekly Earnings: PB: Social Science & Humanities Research data was reported at 1,236.670 USD in May 2018. This records a decrease from the previous number of 1,277.350 USD for Apr 2018. United States Avg Weekly Earnings: PB: Social Science & Humanities Research data is updated monthly, averaging 1,204.960 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 1,366.750 USD in Aug 2009 and a record low of 982.940 USD in May 2012. United States Avg Weekly Earnings: PB: Social Science & Humanities Research 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.

Research and development (R&D) spending was forecast to reach over 2.47 trillion U.S. dollars globally in 2022 (once local currencies are converted for purchasing power parity). This compares to around one trillion U.S. dollars in 2005, and around 555 billion U.S. dollars in 1996. Spending decreased somewhat in 2020 following the outbreak of COVID-19, but increased again in 2021 and was forecast to do so in 2022 too.

United States AHE: sa: PW: PB: Social Science & Humanities Research data was reported at 44.560 USD in Dec 2024. This records a decrease from the previous number of 44.820 USD for Nov 2024. United States AHE: sa: PW: PB: Social Science & Humanities Research data is updated monthly, averaging 24.270 USD from Jan 1990 (Median) to Dec 2024, with 420 observations. The data reached an all-time high of 45.130 USD in Oct 2024 and a record low of 13.620 USD in Feb 1990. United States AHE: sa: PW: PB: Social Science & Humanities Research 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.G071: Current Employment Statistics Survey: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

The interview data was gathered for a project that investigated the practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

The field of Social Sciences has been notoriously known for valuing the contextual component of data and increasingly entertaining more quantitative and computational approaches to research in response to the prevalence of data literacy skills needed to navigate both personal and professional contexts. Thus, this study becomes particularly timely to identify current instructors’ practi..., The project followed a qualitative and exploratory approach to understand current practices of faculty teaching with data. The study was IRB approved and was exempt by the UCSB’s Office of Research in July 2020 (Protocol 1-20-0491).Â

The identification and recruitment of potential participants took into account the selection criteria pre-established by Ithaka S+R: a) instructors of courses within the Social Sciences, considering the field as broadly defined, and making the best judgment in cases the discipline intersects with other fields; b) instructors who teach undergraduate courses or courses where most of the students are at the undergraduate level; c) instructors of any rank, including adjuncts and graduate students; as long as they were listed as instructors of record of the selected courses; d) instructors who teach courses were students engage with quantitative/computational data.Â

The sampling process followed a combination of strategies to more easily identify instructo..., The data folder contains 10Â pdf files with de-identified transcriptions of the interviews and the pdf files with the recruitment email and the interview guide.Â

About this dataset

Context

The dataset tabulates the population of New Point by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for New Point. The dataset can be utilized to understand the population distribution of New Point by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in New Point. 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 New Point.

Key observations

Largest age group (population): Male # 60-64 years (26) | Female # 40-44 years (16). 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 New Point population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the New Point is shown in the following column.
• Population (Female): The female population in the New Point 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 New Point 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 New Point Population by Gender. You can refer the same here

The United States is the leading country worldwide in terms of spending on research and development (R&D), with R&D expenditure exceeding 760 billion purchasing power parity (PPP) U.S. dollars. China is invested about 620 billion U.S. dollars into R&D. Health and technology Overall, health and technology dominate R&D spending globally. In 2022, health constituted nearly 20% of all R&D spending, while hardware producers accounted for over 22% and software producers accounted for over 20%. Tech companies such as Meta, Amazon, and Alphabet contribute massively to tech spending, while spending continues to grow in areas such as medical technology and pharmaceuticals. Other sources of R&D spending Other sources of R&D spending include the automotive industry, chemicals, and manufacturing. Notably, within the automotive industry, the EU leads in spending, contributing nearly 61 billion euros to the 145 billion euros spent on automotive R&D globally. By company, Volkswagen spent the most at 15.6 billion U.S. dollars, while in the United States, Ford spent the most on R&D at 7.6 billion U.S. dollars.

About this dataset

Context

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

Key observations

There is a slight majority of male population, with 50.69% 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 Katie is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Katie 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 Katie Population by Race & Ethnicity. You can refer the same here

The Low Frequency AC-DC Current Probe market plays a crucial role in various industries, enabling accurate measurement and monitoring of electrical currents in both AC and DC systems. These specialized probes are essential tools for engineers and technicians in fields such as telecommunications, automotive, manufact

United States Employment: NF: PB: Social Science & Humanities Research data was reported at 68.000 Person th in May 2018. This records an increase from the previous number of 67.400 Person th for Apr 2018. United States Employment: NF: PB: Social Science & Humanities Research data is updated monthly, averaging 60.800 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 71.700 Person th in May 2002 and a record low of 52.300 Person th in Jan 1991. United States Employment: NF: PB: Social Science & Humanities Research 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.G024: Current Employment Statistics Survey: Employment: Non Farm.