About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in New Britain. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2022

Based on our analysis ACS 2022 1-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In New Britain, the median income for all workers aged 15 years and older, regardless of work hours, was $31,096 for males and $29,418 for females.

Based on these incomes, we observe a gender gap percentage of approximately 5%, indicating a significant disparity between the median incomes of males and females in New Britain. Women, regardless of work hours, still earn 95 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

- Full-time workers, aged 15 years and older: In New Britain, among full-time, year-round workers aged 15 years and older, males earned a median income of $50,848, while females earned $42,515, leading to a 16% gender pay gap among full-time workers. This illustrates that women earn 84 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that New Britain offers better opportunities for women in non-full-time positions.

https://i.neilsberg.com/ch/new-britain-ct-income-by-gender.jpeg" alt="New Britain, CT gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Britain median household income by gender. You can refer the same here

Average weekly earnings at sector level headline estimates, Great Britain, monthly, seasonally adjusted. Monthly Wages and Salaries Survey.

Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time.

This dataset was created and deposited onto the University of Sheffield Online Research Data repository (ORDA) on 23-Jun-2023 by Dr. Matthew S. Hanchard, Research Associate at the University of Sheffield iHuman Institute. The dataset forms part of three outputs from a project titled ‘Fostering cultures of open qualitative research’ which ran from January 2023 to June 2023:

· Fostering cultures of open qualitative research: Dataset 1 – Survey Responses · Fostering cultures of open qualitative research: Dataset 2 – Interview Transcripts · Fostering cultures of open qualitative research: Dataset 3 – Coding Book

The project was funded with £13,913.85 of Research England monies held internally by the University of Sheffield - as part of their ‘Enhancing Research Cultures’ scheme 2022-2023.

The dataset aligns with ethical approval granted by the University of Sheffield School of Sociological Studies Research Ethics Committee (ref: 051118) on 23-Jan-2021. This includes due concern for participant anonymity and data management.

ORDA has full permission to store this dataset and to make it open access for public re-use on the basis that no commercial gain will be made form reuse. It has been deposited under a CC-BY-NC license. Overall, this dataset comprises:

· 15 x Interview transcripts - in .docx file format which can be opened with Microsoft Word, Google Doc, or an open-source equivalent.

All participants have read and approved their transcripts and have had an opportunity to retract details should they wish to do so.

Participants chose whether to be pseudonymised or named directly. The pseudonym can be used to identify individual participant responses in the qualitative coding held within the ‘Fostering cultures of open qualitative research: Dataset 3 – Coding Book’ files.

For recruitment, 14 x participants we selected based on their responses to the project survey., whilst one participant was recruited based on specific expertise.

· 1 x Participant sheet – in .csv format which may by opened with Microsoft Excel, Google Sheet, or an open-source equivalent.

The provides socio-demographic detail on each participant alongside their main field of research and career stage. It includes a RespondentID field/column which can be used to connect interview participants with their responses to the survey questions in the accompanying ‘Fostering cultures of open qualitative research: Dataset 1 – Survey Responses’ files.

The project was undertaken by two staff:

Co-investigator: Dr. Itzel San Roman Pineda ORCiD ID: 0000-0002-3785-8057 i.sanromanpineda@sheffield.ac.uk Postdoctoral Research Assistant Labelled as ‘Researcher 1’ throughout the dataset

Principal Investigator (corresponding dataset author): Dr. Matthew Hanchard ORCiD ID: 0000-0003-2460-8638 m.s.hanchard@sheffield.ac.uk Research Associate iHuman Institute, Social Research Institutes, Faculty of Social Science Labelled as ‘Researcher 2’ throughout the dataset

Gross Domestic Product (GDP) is one of the best known indicators of economic activity and is widely used to monitor economic performance. GDP statistics for Scotland are produced by the Scottish Government and have been designated as National Statistics. This dataset contains statistics for the output approach to GDP and growth in real terms, and includes results for the whole economy (Total GDP) and industry sectors. GDP can also be broken down using the income and expenditure approaches, which are available as separate datasets. There are two updates to the output by industry statistics each quarter. The First Estimate of GDP growth is published around 80 days after the quarter’s end, and an updated second estimate is published in the Quarterly National Accounts around 120 days after the quarter’s end. The First Estimate of GDP statistics will be published on this website as open data; the Second Estimate will not currently be available as open data, but will be available on the Scottish Government website. Results for previous periods are also open to revision each quarter. Further details on Scottish GDP statistics, including methodology notes and the revisions policy, are available. The Industry Sector dimension in this dataset contains the broad industry sectors used on GDP statistics for Scotland the UK. These are based on industry sections from the Standard Industrial Classification (SIC, 2007). Further information can be found here The Measure Type dimension in this dataset contains four GDP measures, detailed below. The index measure is rounded to 4 decimal places and the growth rate measures are rounded to 1 decimal place. It is not always possible to replicate the published growth rates using rounded data, but all results are also available unrounded in the downloadable spreadsheets from the latest publication. • 4Q-on-4Q is the percentage change (growth rate) for the latest four quarters compared to the previous four non-overlapping quarters. This rolling annual growth rate gives a smoothed measure of recent trends. This growth rate is calculated from the Index measure. • Index represents the level of output in real, or volume, terms for each industry or total GDP, relative to the base year (2019). An index value of more than 100 means that output is higher than in the base year, and a value of less than 100 means that output is lower than in the base year. • q-on-q is the percentage change (growth rate) for the latest quarter compared to the previous quarter. This quarterly growth rate is usually taken as the headline measure of GDP growth. This growth rate is calculated from the Index measure. • q-on-q year ago is the percentage change (growth rate) for the latest quarter compared to the same quarter in the previous year. This growth rate over the year is usually compared to other statistics such as earnings or price inflation. This growth rate is calculated from the Index measure. The Reference Period dimension relates to standard calendar quarters. Quarter 1 refers to the period from January to March, Quarter 2 refers to April to June, Quarter 3 refers to July to September, and Quarter 4 refers to October to December. The Reference Area dimension for this dataset only contains results for Scotland, with no breakdowns to other areas. In this dataset, all results relate to Scotland’s onshore economy and do not include the output of offshore oil and gas extraction in Scottish Adjacent Waters. Each industry sector is indexed to make them comparable. For each sector, the value during 2019 is taken as the base year, and given the value of 100. All indexed values are chainlinked volume measures, and given relative to the base year.

To speak to a real person at Etihad, the best option is to call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). When you dial +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), follow the automated menu until you're given the option to speak with a representative. If you don’t hear that option right away, try saying “agent” or pressing “0” during the menu. This usually triggers the system to connect you to a live person. Calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) gives you direct access to someone who can help with flight changes, baggage issues, cancellations, or refund requests. For faster service, have your booking number and personal details ready. If your issue isn’t resolved the first time, don’t hesitate to call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) again. It’s helpful to call during non-peak hours, like early morning or late evening. Etihad values customer satisfaction, and +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is your best line to getting personal, real-time assistance from a trained representative.

Talking to a real person at Etihad is easy—just call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). This number, +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), connects you directly with Etihad’s customer service team. After dialing, you’ll hear an automated menu; select the appropriate options, or simply press “0” or say “agent” to bypass the recording. Etihad’s phone support via +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is available to assist with flight rebookings, seat upgrades, refund issues, or special requests. The representatives are trained to handle everything from ticketing to travel disruptions. Be sure to have your reservation number and travel details ready when calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) to avoid delays. If your call is disconnected or unresolved, don’t worry—just call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) again and request escalation. Many travelers prefer this method because it’s fast, personal, and efficient. Instead of searching online for hours, reach a real person at Etihad by dialing +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) for immediate help.

To reach a real person at Etihad, all you need to do is call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). This number connects you with a live agent who can assist with your travel needs. When you call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), follow the voice prompts, or try pressing “0” repeatedly to skip the automated system. You can also say “representative” or “agent” to get connected faster. Etihad customer service agents at +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) are available to help with flight bookings, refunds, lost baggage, and more. If you're calling about a past flight or future reservation, have your details ready to speed things up. You may need to call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) during off-peak hours to reduce wait time. The agents are polite, efficient, and dedicated to solving problems quickly. For a real-time conversation, calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is your best option to avoid delays and receive direct assistance from an Etihad team member.

If you're trying to talk to a real person at Etihad, simply dial +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). The number +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) connects you to a live representative who can provide personalized assistance. When you call, listen carefully to the menu and either press the key for customer service or say “agent” to be directed immediately. Many travelers prefer speaking to a person rather than navigating endless automated systems, and +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is the fastest way to do that with Etihad. You’ll get help with flight changes, baggage claims, refunds, and general inquiries. If your issue is complex, the representative can escalate it to a supervisor. If you get disconnected, don’t hesitate to call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) again. Make sure to have your booking reference and passport details ready for quicker service. By calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), you ensure that your concern is addressed promptly by a qualified agent who understands your needs.

Need to talk to a real person at Etihad? Just call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). When you call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), you’ll reach an automated system, but you can say “customer service” or “representative” to be connected to a live agent. The team at +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is available to help with flight changes, upgrade requests, or problems with your booking. Many customers find calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) more effective than using the website or mobile app, especially for urgent travel needs. If you're experiencing issues with refunds or rescheduling, a real person can guide you better than an automated system. You may need to wait a few minutes, but +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) will eventually connect you to someone who can assist. If you’re disconnected or the line is busy, just try +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) again later. For the fastest and most direct way to speak to Etihad support, +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is your go-to number.

To speak with a real person at Etihad, the most reliable method is calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US). This number, +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), will connect you with a live customer service agent who can help with reservations, cancellations, delays, or any other travel-related concerns. Once you call +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US), listen to the automated menu and choose the option for customer service, or press “0” repeatedly until you're transferred. It helps to call during non-peak hours for shorter wait times. Have your ticket number and ID ready when you dial +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) to make the process faster. If you’re calling about an urgent issue like missed flights or denied boarding, an agent at +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) can act quickly. Etihad takes customer service seriously, and +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) is the most efficient way to get live support. Don’t rely only on online forms—calling +44.(203)+900-0080(UK) or +1.(888)+800-9117 (US) ensures your problem is heard and handled in real-time.

Wages in the United Kingdom increased 5 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United Kingdom Average Weekly Earnings Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of cancer (in persons of all ages). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to cancer (in persons of all ages).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (all ages) with cancer was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with cancer was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with cancer, within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have cancerB) the NUMBER of people within that MSOA who are estimated to have cancerAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have cancer, compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from cancer, and where those people make up a large percentage of the population, indicating there is a real issue with cancer within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of cancer, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of cancer.TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.MSOA boundaries: © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021.Population data: Mid-2019 (June 30) Population Estimates for Middle Layer Super Output Areas in England and Wales. © Office for National Statistics licensed under the Open Government Licence v3.0. © Crown Copyright 2020.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital; © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021. © Crown Copyright 2020.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Abstract copyright UK Data Service and data collection copyright owner. The New Earnings Survey (NES) is an annual survey of the earnings of employees in Great Britain. Its primary purpose is to obtain information about the levels, distribution and make-up of earnings, and for the collective agreements that cover them. The NES is designed to represent all categories of employees in businesses of all kinds and sizes. It provides a large amount of information on earnings and hours (including bonuses, overtime, etc) as well as industry information derived from the Inter-Departmental Business Register. It provides no information on personal characteristics of the employee apart from age and gender. Most variables are collected each year, although a few additional questions asked each year may or may not be asked in other years. The earnings, hours of work and other information relate to a specified week in April of each year. The NES sampling frame is mainly supplied by Inland Revenue records. It is based largely on a one per cent sample of employees who are members of Pay-As-You-Earn (PAYE) income tax schemes. The PAYE sample is supplemented by data provided by large employers, using extracts from their payroll systems. A survey form is sent to employers, and completion is compulsory under the Statistics of Trade Act 1947. Some large businesses make automatic submissions direct from their electronic records. Certain categories of employees are not selected: for example the Armed Forces, those employed in Enterprise Zones, private domestic service workers, occupational pensioners, non-salaried directors, those employed oversees, those working for their spouses, and clergymen holding pastoral appointments. The NES was replaced by the Annual Survey of Hours and Earnings (UK Data Archive SN 6689) in 2004. Further information on the NES can be found on the Office for National Statistics' (ONS) New Earnings Survey web page. There are a number of issues and inconsistencies associated with the NES data. Users are advised to read the documentation carefully before using the dataset. For example, ONS advise for safety reasons that only data from 1998 onwards should be used because 1998 was the first year that annual earnings were validated properly and published. Geographical references: postcodes The postcodes available in these data from 1996 are pseudo-anonymised postcodes. The real postcodes are not available due to the potential risk of identification of the observations. However, these replacement postcodes retain the inherent nested characteristics of real postcodes, and will allow researchers to aggregate observations to other geographic units, e.g. wards, super output areas, etc. In the dataset, the variable of the replacement postcode is 'new_PC'. Main Topics: The NES collects the following data for employees in all industries and occupations and for the major national collective agreements:levels, distributions and make-up of earningshours workedindustryoccupationplace of workgender age Simple random sample One per cent sample of individuals from National Insurance records

We create a synthetic administrative dataset to be used in the development of the R package for calculating quality indicators for administrative data (see: https://github.com/sook-tusk/qualadmin) that mimic the properties of a real administrative dataset according to specifications by the ONS. Taking over 1 million records from a synthetic 1991 UK census dataset, we deleted records, moved records to a different geography and duplicated records to a different geography according to pre-specified proportions for each broad ethnic group (White, Non-white) and gender (males, females). The final size of the synthetic administrative data was 1033664 individuals.National Statistical Institutes (NSIs) are directing resources into advancing the use of administrative data in official statistics systems. This is a top priority for the UK Office for National Statistics (ONS) as they are undergoing transformations in their statistical systems to make more use of administrative data for future censuses and population statistics. Administrative data are defined as secondary data sources since they are produced by other agencies as a result of an event or a transaction relating to administrative procedures of organisations, public administrations and government agencies. Nevertheless, they have the potential to become important data sources for the production of official statistics by significantly reducing the cost and burden of response and improving the efficiency of such systems. Embedding administrative data in statistical systems is not without costs and it is vital to understand where potential errors may arise. The Total Administrative Data Error Framework sets out all possible sources of error when using administrative data as statistical data, depending on whether it is a single data source or integrated with other data sources such as survey data. For a single administrative data, one of the main sources of error is coverage and representation to the target population of interest. This is particularly relevant when administrative data is delivered over time, such as tax data for maintaining the Business Register. For sub-project 1 of this research project, we develop quality indicators that allow the statistical agency to assess if the administrative data is representative to the target population and which sub-groups may be missing or over-covered. This is essential for producing unbiased estimates from administrative data. Another priority at statistical agencies is to produce a statistical register for population characteristic estimates, such as employment statistics, from multiple sources of administrative and survey data. Using administrative data to build a spine, survey data can be integrated using record linkage and statistical matching approaches on a set of common matching variables. This will be the topic for sub-project 2, which will be split into several topics of research. The first topic is whether adding statistical predictions and correlation structures improves the linkage and data integration. The second topic is to research a mass imputation framework for imputing missing target variables in the statistical register where the missing data may be due to multiple underlying mechanisms. Therefore, the third topic will aim to improve the mass imputation framework to mitigate against possible measurement errors, for example by adding benchmarks and other constraints into the approaches. On completion of a statistical register, estimates for key target variables at local areas can easily be aggregated. However, it is essential to also measure the precision of these estimates through mean square errors and this will be the fourth topic of the sub-project. Finally, this new way of producing official statistics is compared to the more common method of incorporating administrative data through survey weights and model-based estimation approaches. In other words, we evaluate whether it is better 'to weight' or 'to impute' for population characteristic estimates - a key question under investigation by survey statisticians in the last decade. This is a synthetic administrative dataset with only 6 variables to enable the calculation of quality indicators in the R package: https://github.com/sook-tusk/qualadmin See also the user manual. The dataset was created from a 1991 synthetic UK census dataset containing over 1 million records by deleting, moving and duplicating records across geographies according to pre-specified proportions within broad ethnic group and gender. The geography variable includes 6 local authorities but they are completely anonymized and labelled 1,2..6. Other variables are (number of categories in parentheses): sex (2), age groups (14), ethnic groups (5) and employment (3). The final size of the synthetic administrative data is 1033664 individuals. The description of the variables are in the data dictionary that is uploaded with the data.

The Royal Caribbean cancellation phone number is not provided in the search results. However, it's recommended to call their customer service line at +1-855-732-4023 USA or +44-289-708-0062. You can also manage your booking and potentially find cancellation information on their website.

To cancel a Royal Caribbean cruise reservation, you can contact Royal Caribbean directly by phone. The support team can be reached at +1-855-732-4023 USA or +44-289-708-0062. You can speak with a representative to process your request and confirm any applicable fees or refunds.

How to cancel Royal Caribbean cruise by phone?

To cancel your Royal Caribbean cruise by phone, you can call their customer support line at +1-855-732-4023 USA or +44-289-708-0062. Alternatively, you can use the number +1-855-732-4023 USA or +44-289-708-0062, which is also listed for general customer service inquiries and post-cruise assistance.

If you wish to change your ship or sail date, and you booked directly with Royal Caribbean, you can contact their Consumer Outreach team at +1-855-732-4023 USA or +44-289-708-0062.

How to cancel Royal Caribbean cruise online?

To cancel a Royal Caribbean cruise booking, you can contact their customer service directly. The best phone number to call for cancellations and reservation changes is +1-855-732-4023 USA or +44-289-708-0062. This number is for individual reservations in the US and Canada and is available Monday-Sunday, 7 am-2 am EST. You can also try calling the general Royal Caribbean customer service number ++1-855-732-4023 USA or +44-289-708-0062, which is available 24/7.

The best phone number to contact Royal Caribbean customer service in the USA for refund inquiries is +1-855-732-4023 USA or +44-289-708-0062. This is their general customer service number for US and Canada.

Alternatively, you can also use +1-855-732-4023 USA or +44-289-708-0062 as another option mentioned in the search results.

If you are a Crown & Anchor Society member, you can also call +1-855-732-4023 USA or +44-289-708-0062.

To cancel your Royal Caribbean cruise by phone, you can call their customer support line at +1-855-732-4023. This number is available for individual reservations and general customer service from Monday to Sunday, 7 am to 2 am (EST). Alternatively, you can call +1-855-732-4023 USA or +44-289-708-0062 to speak with a representative about your cancellation.

You can contact Royal Caribbean Customer Service through several channels, depending on your needs.

Phone:

. General Customer Service: Call +1-855-732-4023 USA or +44-289-708-0062 UK. Available Monday-Friday 8am-11pm EST, and Saturday-Sunday 9am-6pm EST. . Individual Reservations: Call +1-855-732-4023 USA or +44-289-708-0062 UK. Available Mon-Sun 7am-2am (EST). . Group Reservations (8+ staterooms): Call +1-855-732-4023 USA or +44-289-708-0062. Available Mon-Fri 9am-7pm EST and Sat 9am-6pm EST. . Post Cruise Assistance: Call +1-855-732-4023 USA or +44-289-708-0062 UK or text 24 hours/7 days a week. Phone lines available Mon-Thu 24 hours, Fri 12am-9pm, Sat 9am-6pm, Sun 9am-12am (EST). . Air2Sea Arrangements: Call +1-855-732-4023 USA or +44-289-708-0062 UK. Available 24/7. . Day of Sailing help: Call +1-855-732-4023 USA or +44-289-708-0062 UK (Int'l). Available 24/7. . Online Assistance: Call +1-855-732-4023 USA or +44-289-708-0062 UK. Available Mon-Fri 8am-11pm EST and Sat-Sun 9am-6pm EST.

What is the phone number for Royal Caribbean cancel?

For assistance with canceling your Royal Caribbean cruise, you can call their support team at +1-855-732-4023 USA or +44-289-708-0062 UK. To change a non-refundable deposit fare: You can contact their Consumer Outreach team at +1-855-732-4023 USA or +44-289-708-0062 UK.

Royal Caribbean customer service hours

Royal Caribbean provides several ways to contact customer service with varying hours. You can reach them through online assistance at +1-855-732-4023 USA or +44-289-708-0062 with specific hours on weekdays and weekends.

Royal Caribbean cruise cancellation phone number

To cancel your Royal Caribbean cruise by phone, you can call their customer support line at +1-855-732-4023 USA or +44-289-708-0062. Alternatively, you can use the number +1-855-732-4023 USA or +44-289-708-0062, which is also listed for general customer service inquiries and post-cruise assistance.

What is the Royal Caribbean cancellation number?

The main Royal Caribbean phone number for customer service, which can be used for cancellations, is +1-855-732-4023 USA or +44-289-708-0062 UK. You can also contact them via email or through a travel agent.

Based on the search results, the phone number provided for Royal Caribbean cruise cancellations is +1-855-732-4023 USA or +44-289-708-0062 UK.

You can cancel your Royal Caribbean cruise through various channels +1-855-732-4023 USA or +44-289-708-0062 UK depending on how you booked your trip. To cancel your cruise, call the support team at +1-855-732-4023 USA or +44-289-708-0062 UK and speak with a representative to process your request +1-855-732-4023 USA or +44-289-708-0062 UK and confirm any applicable fees or refunds.

What number do I call to cancel my Royal Caribbean cruise?

To cancel a Royal Caribbean cruise, you can call their customer service line at +1-855-732-4023 USA or +44-289-708-0062 UK. You can also contact them via email at book@rccl.ae, according to Royal Caribbean.

Guests who booked directly through Royal Caribbean may be able to cancel their cruise via the “Manage Reservation” section of the official website +1-855-732-4023 USA or +44-289-708-0062 UK though some restrictions may apply.

Can you get a better deal by calling Royal Caribbean?

Yes, calling Royal Caribbean directly can potentially get you a better deal+1-855-732-4023, especially with their Best Price Guarantee program. By speaking with a live agent+1-855-732-4023, you might gain access to exclusive promotions, discounts, or onboard credits not readily available online. Additionally+1-855-732-4023, their Best Price Guarantee allows you to reprice your cruise if the price drops before the final payment date, potentially saving you money.

The "3-1-1 rule" on Royal Caribbean+1-855-732-4023, which mirrors TSA regulations, pertains to the amount of liquids allowed in your carry-on luggage. It means each passenger can bring one quart-sized+1-855-732-4023, clear, resealable plastic bag containing liquids, aerosols, gels, and creams, with each container limited to 3.4 ounces (100ml) or less.

How do you call someone on Royal Caribbean?

To call someone on a Royal Caribbean cruise, you can use the stateroom phone to make a "ship-to-shore" call by dialing +1-855-732-4023. Friends and family can also reach guests on the ship using this number +1-855-732-4023, but calls incur a per-minute fee charged to the recipient's onboard account.

Royal Caribbean Emergency Contact: Your friends and family can contact the ship directly by calling a dedicated phone number, such as +1-855-732-4023. You should provide those who might need to reach you with the ship name, sail date, and your stateroom number to help them connect to the ship when calling +1-855-732-4023.

What is the phone number for Royal Caribbean booking?

You can reach out to your travel advisor or contact us at +1-855-732-4023 to learn more about this pricing program. What is the Royal Caribbean Best Price Guarantee Program? When making your reservation with Royal Caribbean, you can book with confidence knowing you're protected by our Best Price Guarantee program.

Royal Caribbean provides a dedicated phone number for Individual Reservations in the US and Canada: +1-855-732-4023. They are available from 7 am to 2 am EST, seven days a week.

If you are sailing with 8 or more staterooms and need to make a Group Reservation, you can call +1-855-732-4023. Their hours are Monday through Friday, 9 am to 7 pm EST, and on Saturday from 9 am to 6 pm EST.

For other customer service inquiries, you can use the toll-free number: +1-855-732-4023. This number is for general customer service needs.

For the Crown and Anchor Society, there's a dedicated line for Diamond Plus or Pinnacle Club members at +1-855-732-4023.

Can you get a better deal by calling Royal Caribbean?

Yes, calling Royal Caribbean directly can potentially help you secure a better deal +1-855-732-4023 USA or +44-289-708-0062 UK, including exclusive promotions, discounts, or upgrades not available online, or help with repricing your cruise if a better price emerges.

Can you cancel a Royal Caribbean cruise for free?

You have up to 75 days before your sailing date to cancel a Royal Caribbean cruise for a full refund (+1-855-732-4023)). For 1 to 4-night cruises +1-855-732-4023 USA or +44-289-708-0062 UK, the deadline is 60 days.

The free phone number for Royal Caribbean customer service, including for refund inquiries, is +1-855-732-4023 USA or +44-289-708-0062 UK. You can also find other contact options, including live chat, on their website.

For questions regarding refunds for your Royal Caribbean cruise, you can call their customer service number at +1-855-732-4023 USA or +44-289-708-0062 UK.

Company Datasets for valuable business insights!

Discover new business prospects, identify investment opportunities, track competitor performance, and streamline your sales efforts with comprehensive Company Datasets.

These datasets are sourced from top industry providers, ensuring you have access to high-quality information:

• Owler: Gain valuable business insights and competitive intelligence. -AngelList: Receive fresh startup data transformed into actionable insights. -CrunchBase: Access clean, parsed, and ready-to-use business data from private and public companies. -Craft.co: Make data-informed business decisions with Craft.co's company datasets. -Product Hunt: Harness the Product Hunt dataset, a leader in curating the best new products.

We provide fresh and ready-to-use company data, eliminating the need for complex scraping and parsing. Our data includes crucial details such as:

• Company name;
• Size;
• Founding date;
• Location;
• Industry;
• Revenue;
• Employee count;
• Competitors.

You can choose your preferred data delivery method, including various storage options, delivery frequency, and input/output formats.

Receive datasets in CSV, JSON, and other formats, with storage options like AWS S3 and Google Cloud Storage. Opt for one-time, monthly, quarterly, or bi-annual data delivery.

With Oxylabs Datasets, you can count on:

• Fresh and accurate data collected and parsed by our expert web scraping team.
• Time and resource savings, allowing you to focus on data analysis and achieving your business goals.
• A customized approach tailored to your specific business needs.
• Legal compliance in line with GDPR and CCPA standards, thanks to our membership in the Ethical Web Data Collection Initiative.

Pricing Options:

Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

Experience a seamless journey with Oxylabs:

• Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
• Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
• Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

Unlock the power of data with Oxylabs' Company Datasets and supercharge your business insights today!

The dataset contains 39148 years of sea level data from 1355 station records, with some stations having alternative versions of the records provided from different sources. GESLA-2 data may be obtained from www.gesla.org. The site also contains the file format description and other information. The text files contain headers with lines of metadata followed by the data itself in a simple column format. All the tide gauge data in GESLA-2 have hourly or more frequent sampling. The basic data from the US National Atmospheric and Oceanic Administration (NOAA) are 6-minute values but for GESLA-2 purposes we instead settled on their readily-available 'verified hourly values'. Most UK records are also hourly values up to the 1990s, and 15-minute values thereafter. Records from some other sources may have different sampling, and records should be inspected individually if sampling considerations are considered critical to an analysis. The GESLA-2 dataset has global coverage and better geographical coverage that the GESLA-1 with stations in new regions (defined by stations in the new dataset located more than 50 km from any station in GESLA-1). For example, major improvements can be seen to have been made for the Mediterranean and Baltic Seas, Japan, New Zealand and the African coastline south of the Equator. The earliest measurements are from Brest, France (04/01/1846) and the latest from Cuxhaven, Germany and Esbjerg, Denmark (01/05/2015). There are 29 years in an average record, although the actual number of years varies from only 1 at short-lived sites, to 167 in the case of Brest, France. Most of the measurements in GESLA-2 were made during the second half of the twentieth century. The most globally-representative analyses of sea level variability with GESLA-2 will be those that focus on the period since about 1970. Historically, delayed-mode data comprised spot values of sea level every hour, obtained from inspection of the ink trace on a tide gauge chart. Nowadays tide gauge data loggers provide data electronically. Data can be either spot values, integrated (averaged) values over specified periods (e.g. 6 minutes), or integrated over a specified period within a longer sampling period (e.g. averaged over 3 minutes every 6 minutes). The construction of this dataset is fundamental to research in sea level variability and also to practical aspects of coastal engineering. One component is concerned with encouraging countries to install tide gauges at locations where none exist, to operate them to internationally agreed standards, and to make the data available to interested users. A second component is concerned with the collection of data from the global set of tide gauges, whether gauges have originated through the GLOSS programme or not, and to make the data available. The records in GESLA-2 will have had some form of quality control undertaken by the data providers. However, the extent to which that control will have been undertaken will inevitably vary between providers and with time. In most cases, no further quality control has been made beyond that already undertaken by the data providers. Although there are many individual contributions, over a quarter of the station-years are provided by the research quality dataset of UHSLC. Contributors include: British Oceanographic Data Centre; University of Hawaii Sea Level Center; Japan Meteorological Agency; US National Oceanic and Atmospheric Administration; Puertos del Estado, Spain; Marine Environmental Data Service, Canada; Instituto Espanol de Oceanografica, Spain; idromare, Italy; Swedish Meteorological and Hydrological Institute; Federal Maritime and Hydrographic Agency, Germany; Finnish Meteorological Institute; Service hydrographique et oceanographique de la Marine, France; Rijkswaterstaat, Netherlands; Danish Meteorological Institute; Norwegian Hydrographic Service; Icelandic Coastguard Service; Istituto Talassographico di Trieste; Venice Commune, Italy;

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Calendar Year Dataset, 2022, is designed for analysts to conduct cross-sectional analysis for the 2022 calendar year. The Calendar Year datasets combine data collected in a specific year from across multiple waves and these are released as separate calendar year studies, with appropriate analysis weights, starting with the 2020 Calendar Year dataset. Each subsequent year, an additional yearly study is released.

The Calendar Year data is designed to enable timely cross-sectional analysis of individuals and households in a calendar year. Such analysis can, however, only involve variables that are collected in every wave (excluding rotating content, which is only collected in some of the waves). Due to overlapping fieldwork, the data files combine data collected in the three waves that make up a calendar year. Analysis cannot be restricted to data collected in one wave during a calendar year, as this subset will not be representative of the population. Further details and guidance on this study can be found in the document 9333_main_survey_calendar_year_user_guide_2022.

These calendar year datasets should be used for cross-sectional analysis only. For those interested in longitudinal analyses using Understanding Society please access the main survey datasets: End User Licence version or Special Licence version.

Understanding Society: the UK Household Longitudinal Study, started in 2009 with a general population sample (GPS) of UK residents living in private households of around 26,000 households and an ethnic minority boost sample (EMBS) of 4,000 households. All members of these responding households and their descendants became part of the core sample who were eligible to be interviewed every year. Anyone who joined these households after this initial wave was also interviewed as long as they lived with these core sample members to provide the household context. At each annual interview, some basic demographic information was collected about every household member, information about the household is collected from one household member, all 16+-year-old household members are eligible for adult interviews, 10-15-year-old household members are eligible for youth interviews, and some information is collected about 0-9 year-olds from their parents or guardians. Since 1991 until 2008/9 a similar survey, the British Household Panel Survey (BHPS), was fielded. The surviving members of this survey sample were incorporated into Understanding Society in 2010. In 2015, an immigrant and ethnic minority boost sample (IEMBS) of around 2,500 households was added. In 2022, a GPS boost sample (GPS2) of around 5,700 households was added. To know more about the sample design, following rules, interview modes, incentives, consent, and questionnaire content, please see the study overview and user guide.

Co-funders

In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.

End User Licence and Special Licence versions:

There are two versions of the Calendar Year 2022 data. One is available under the standard End User Licence (EUL) agreement (SN 9333), and the other is a Special Licence (SL) version (SN 9334). The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see document 9333_eul_vs_sl_variable_differences for more details). Users are advised first to obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (EUL) and 6931 (SL).

Low- and Medium-level geographical identifiers produced for the mainstage longitudinal dataset can be used with this Calendar Year 2022 dataset, subject to SL access conditions. See the User Guide for further details.

Suitable data analysis software

These data are provided by the depositor in Stata format. Users are strongly advised to analyse them in Stata. Transfer to other formats may result in unforeseen issues. Stata SE or MP software is needed to analyse the larger files, which contain about 1,800 variables.

15 smart sensors were installed on Mill Road and surrounding streets to record numbers of pedestrians, bicycles, cars and other vehicles. The data being collated and analysed by the Smart Cambridge programme will help the Greater Cambridge Partnership understand how people use the road network.

Data will be released monthly for these locations until the end of 2020. Please note that due to the level of insight that can be gained from these sensors, additional sensors in more locations have been installed in Cambridge since the summer of 2019. Some sensors will remain beyond 2020 in strategic locations and the network is expected to grow. Data for those more permanent sites, outside of the Mill Road project will be published here: https://data.cambridgeshireinsight.org.uk/dataset/cambridge-city-smart-s...

Mill Road Bridge was closed for eight weeks from 1 July 2019 for crucial work being carried out to improve rail services. Pedestrians and cyclists will still be able to cross the railway for most of the working time.

A high concentration of sensors were installed for approximately 18 months to gather data before the closure, during the time when there is no vehicle traffic coming over Mill Road Bridge and then after the bridge is re-opened. This has allowed engineers to see the impact of the closure on surrounding roads, including on air quality. Keeping the sensors in place for this long has also allowed teams to make greater comparisons, by taking in to account daily, weekly, monthly and annual variations in traffic levels.

The below data release offers counts for each sensor over 1 hour periods. The curent data covers the period 03/06/2019 to 13/12/2020.

Hourly counts are broken down by inbound and outbound journeys. .

Counts are also broken down by vehicle type. This includes:

Pedestrians Cyclists Buses LGV OGV 1 OGV 2 The release also includes a full list of sensor sites with geographic point location data.