This dataset provides Census 2021 estimates for National Statistics Socio-economic Classification (NS-SeC) by sex in Northern Ireland. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

The quality assurance report can be found here

A file that holds the master records for all online training courses nominated for reimbursement.

Data were collected through an online survey and processed to create 95% CI using the BCA bootstrap confidence interval algorithm in MS EXCEL. Construction of confidence interval in MS EXCEL using the BCA bootstrap confidence interval algorithm is earlier not presented in any studies. The macro capabilities of MS EXCEL was utilized for the purpose stated.

The pie chart showcases the distribution of app/software spending by store category in Montserrat, providing insights into how eCommerce stores allocate their resources on the app or software they utilize. Among the store categories, Apparel exhibits the highest spending, with a total expenditure of $1.00K units representing 100.00% of the overall spending. Following closely behind is Gifts & Special Events with a spend of $0.00 units, comprising <0.01% of the total. Sports also contributes significantly with a spend of $0.00 units, accounting for <0.01% of the overall app/software spending. This data sheds light on the investment patterns of eCommerce stores within each category, reflecting their priorities and resource allocation towards app or software solutions.

According to an online survey conducted in February 2025 in the United States, ********* of LinkedIn users held a bachelor degree or equivalent. Additionally, ** percent of LinkedIn users in the U.S. held a masters degree or equivalent.

1. Provides public access to real-time instantatenous water level collected at over 1800 active locations in Canada. These data are collected under a national program jointly administered under federal-provincial and federal-territorial cost-sharing agreements; 2. Provides public access to archived daily water level for stations of interest using search criteria. These data include: daily and monthly mean, max and min of water levels. For some sites, annual peaks and extremes are also recorded. Archived water level data are disseminated online; 3. Provides public access to a MS Access database file containing archived daily water level that users can download to their desktop. These data include: daily and monthly mean, max and min of water level. For some sites, annual peaks and extremes are also recorded. MS Access file is updated quarterly; 4. Provides public access to water level statistics for stations of interest using search criteria.

In Montserrat, the distribution of stores across different platforms presents a dynamic picture of the market.

Dataset

This dataset was created by swdmop

Released under GPL 2

Contents

Table View of Master_OP_EXP - Budgets and Actuals from FY 2016, 2017, 2018, 2019, and FYTD 2020. This View is the data source for Expense Dashboards. Update Schedule: Once per Month.

This chart offers an insightful look at the store count by category in Montserrat. Leading the way is Apparel, with 1 stores, which is 33.33% of the total stores in the region. Next is Gifts & Special Events, contributing 1 stores, or 33.33% of the region's total. Sports also has a notable presence, with 1 stores, making up 33.33% of the store count in Montserrat. This breakdown provides a clear picture of the diverse retail landscape in Montserrat, showcasing the variety and scale of stores across different categories.

This chart provides a detailed overview of the number of Montserrat online retailers by Number of Employee. Most Montserrat stores' Number of Employee are Less than 10, there are 1 stores, which is 50.00% of total. In second place, 1 stores' Number of Employee are 200 to 500, which is 50.00% of total. Meanwhile, 0 stores' Number of Employee are 10 to 20, which is <0.01% of total. This breakdown reveals insights into Montserrat stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

This chart provides a detailed overview of the number of Montserrat online retailers by Monthly Visitors. Most Montserrat stores' Monthly Visitors are Less than 100, there are 1 stores, which is 50.00% of total. In second place, 1 stores' Monthly Visitors are 100K to 1M, which is 50.00% of total. Meanwhile, 0 stores' Monthly Visitors are 100 to 1K, which is <0.01% of total. This breakdown reveals insights into Montserrat stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

Provides public access to real-time instantatenous water level collected at over 1800 active locations in Canada. These data are collected under a national program jointly administered under federal-provincial and federal-territorial cost-sharing agreements; 2. Provides public access to archived daily water level for stations of interest using search criteria. These data include: daily and monthly mean, max and min of water levels. For some sites, annual peaks and extremes are also recorded. Archived water level data are disseminated online; 3. Provides public access to a MS Access database file containing archived daily water level that users can download to their desktop. These data include: daily and monthly mean, max and min of water level. For some sites, annual peaks and extremes are also recorded. MS Access file is updated quarterly; 4. Provides public access to water level statistics for stations of interest using search criteria.

This dataset provides Census 2021 estimates that classify usual residents aged 16 and over (excluding full-time students) in employment the week before the census in Northern Ireland by the distance they travelled to work. The estimates are as at census day, 21 March 2021. Census 2021 took place during the coronavirus (COVID-19) pandemic which will have affected the travel to work and travel to study statistics.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

The quality assurance report can be found here

We propose a procedure associated with the idea of the E-M algorithm for model selection in the presence of missing data. The idea extends the concept of parameters to include both the model and the parameters under the model, and thus allows the model to be part of the E-M iterations. We develop the procedure, known as the E-MS algorithm, under the assumption that the class of candidate models is finite. Some special cases of the procedure are considered, including E-MS with the generalized information criteria (GIC), and E-MS with the adaptive fence (AF; Jiang et al.). We prove numerical convergence of the E-MS algorithm as well as consistency in model selection of the limiting model of the E-MS convergence, for E-MS with GIC and E-MS with AF. We study the impact on model selection of different missing data mechanisms. Furthermore, we carry out extensive simulation studies on the finite-sample performance of the E-MS with comparisons to other procedures. The methodology is also illustrated on a real data analysis involving QTL mapping for an agricultural study on barley grains. Supplementary materials for this article are available online.

This dataset provides Census 2021 estimates that classify households in Northern Ireland by the household lifestage of the Household Reference Person (HRP). The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.