About this dataset

Context

The dataset tabulates the population of New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.

Key observations

The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 82.88% are white, 4.57% are Black or African American, 0.35% are American Indian and Alaska Native, 5.78% are Asian, 0.39% are some other race and 6.02% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the New Britain
• Population: The population of the racial category (excluding ethnicity) in the New Britain is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Britain 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 New Britain Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of England by race. It includes the population of England across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of England across relevant racial categories.

Key observations

The percent distribution of England population by race (across all racial categories recognized by the U.S. Census Bureau): 68.50% are white, 22% are Black or African American, 0.31% are American Indian and Alaska Native, 4.52% are some other race and 4.67% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the England
• Population: The population of the racial category (excluding ethnicity) in the England is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of England 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 England Population by Race & Ethnicity. You can refer the same here

This dataset represents ethnic group (19 tick-box level) by economic activity status and by occupation, for England and Wales combined. The census data are also broken down by age and by sex for each subtopic.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged between 16 to 64 years old only. This is to focus on ethnic groups differences among the working age. Population counts in these tables may be different from other publications which use different age breakdowns.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

For quality information in general, please read more from here.

For specific quality information about labour market, please read more from here

Ocupation counts classifiy people who were in employment between 15 March and 21 March 2021, by the SOC code that represents their current occupation. (Occupation is classified using the Standard Occupation Classification 2020 version). Details of SOC code can be found here.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

Dataset population: Persons

Ethnic group

Ethnic group classifies people according to their own perceived ethnic group and cultural background.

This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the "Irish" response category. This topic was created as part of the commissioned table processing.

This measures percentage point differences in the proportions of each Black Minority and Ethnic (BME) group of young people on youth justice disposals against the proportions of each BME group in the equivalent local population. BME main groups are classified as those main groups in the 2001 census. The ONS latest mid-year estimated figures used for the local youth population by BME group. It is important to do the analysis by each of the ethnic groups and not the overall BME group, otherwise the under-represented groups counter-balance the over-represented groups – giving the false impression there is no over-representation of particular BME groups. Areas would only need to submit values for the number of offenders in each ethnic group, as the local population data would be sourced from ONS to do the required calculations. Young people are those aged 10-17 years.

Dataset population: Persons

Ethnic group

Ethnic group classifies people according to their own perceived ethnic group and cultural background.

This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the 'Irish' response category. This topic was created as part of the commissioned table processing.

National identity

A person's national identity is a self-determined assessment of their own identity with respect to the country or countries with which they feel an affiliation. This assessment of identity is not dependent on legal nationality or ethnic group.

The national identity question included six tick box responses:

• English
• Welsh
• Scottish
• Northern Irish
• British
• Other

Where a person ticked 'Other' they were asked to write in the name of the country. People were asked to tick all options that they felt applied to them. This means that in results relating to national identity people may be classified with a single national identity or a combination of identities.

This dataset brings together all 698 known references to ‘Black’ or possibly Black African heritage people or groups in records of London criminal justice (1720-1841). Each entry includes references to primary sources mentioning the person(s), including in the Old Bailey Proceedings, Ordinary’s Accounts, and Middlesex Criminal Registers. Individuals are trial witnesses, victims, defendants, and people mentioned in passing during testimony. For each entry, a confidence level is offered by the authors, as a person’s ethnicity cannot always be determined with certainty. Evidence for making that judgment is provided. This dataset is useful for anyone interested in Black history in Britain, Black people and justice, or Black London during the age of enslavement.

Significant background material is available on the Old Bailey Online website, which provides additional context for these records. The authors also recommend the following works:

* Kathleen Chater. Untold Histories: Black People in England and Wales during the Period of the British Slave Trade, c. 1660-1807 (Manchester, 2011).
* Norma Myers, Reconstructing the Black Past (Frank Cass, 1996).
* Marika Sherwood. ‘Blacks in the Gordon Riots’, History Today, vol. 47 (1997), 24-28.

Each record includes details on the name of the Black individual(s), as well as information on up to three sources in which he/she/they have been identified, and an indication by the authors on the likelihood the person is actually Black.

Each entry has 17 columns of data, all of which are described in full in the ReadMe.txt file.

Vaccination rates and odds ratios by socio-demographic group among people living in England.

Unequal impact of COVID-19: BAME disproportionality Section 1 (slides 1 – 3): The Public Health England (PHE) review confirms the risk of mortality as a result of covid-19 by ethnicity. Data on access to care and emergency response has been taken from our local VCS partner feedback and indications from local data.) Data on the care workforce by ethnicity was taken from our local data and the Section 2 (Slides 4 – 7) covers demographic information on Black, Asian, and other or mixed ethnic people delivering direct care in the wider social care sector from the Skills for Care 2019 Social Care Workforce Review (note: factors that need to be considered are age, sex, underlying health conditions, ethnicity, and pregnancy.) Information on Camden’s ASC workforce was taken from GLA 2016-based Ethnic Group Projections - mid-2020). Demographic information on people receiving ASC support in Camden has been taken from our local service data. Section 3: (slides 8-15) sets out information on Adult Social Care activity during Covid-19 and looks at data relative to ethnicity including the ASC cohort of Camden’s shielded residents. (Service held data NOT official statistics including qualitative feedback from communities) Section 4: (Slides 16 – 18) shows information related to the Adult Social Care outcomes framework which has provided some information gathered before Covid-19 on the experiences of people who are BAME and in receipt of social care support in Camden.

Unequal impact of COVID-19: BAME disproportionality With the whole country and world waking up to the deeply entrenched structural equalities that have impacted the lives of our Black, Asian and other ethnic Minority communities, there is a collective appreciation that we need to go further to dismantle a system, and create new ones. Local and national evidence shows that people from a Black, Asian or minority ethnic background are disproportionately impacted by Covid-19. In response to this, the council implemented this working group to carry out a rapid 6-week programme to gather evidence of the impacts of Covid-19 and develop actions for supporting our residents during this time and beyond. Intensive work has been underway to understand and take action to address the direct and indirect health impacts of Covid-19 on our Black, Asian and other Ethnic Minority communities in Camden, and to ensure that individuals and communities are protected both now and through the next phase of the pandemic, but also to bring about wider systemic change. This document is us working in the open with you and shows the information that was provided by different service areas to the member-led working group for comment and to develop actions going forward. The Black, Asian and other Ethnic Minority Inequalities and Covid-19 Working Group has benefitted from evidence and the lived experience of our residents, VCS partners, professionals and Members in guiding and shaping the Council’s response from bureaucratic to relational. In this document you will find summaries of the data included in these presentation slides and the relevant links to documents.

About the Dataset:

Amazon is one of the biggest online retailers in the UK. With this dataset, you can get an in-depth idea of what products sell best, which SEO titles generate the most sales, the best price range for a product in a given category, and much more.

It took a lot of time and energy to prepare this original dataset, so don't forget to hit the upvote button! 😊💝

Similar Datasets:

Amazon Canada Products

Amazon India Products

Amazon USA Products

Interesting Task Ideas:

1. Uncover trending product categories and their sales performance.
2. Analyze customer ratings to find top-rated products.
3. Train a product title generator that can generate sales-worthy product titles based on products with the most sales.
4. Gain insight into the best price for any given product based on sales data and competition.
5. Identify which niches are the easiest to make sales in.
6. Gain insights into the general spending habits of online shoppers.
7. Use as a seed dataset for practicing database management and performance optimization.
8. Train (or learn to train) an AI-based search model to recommend Amazon products.

Checkout my other datasets

USA Unemployment Rates by Demographics & Race

USA Hispanic-White Wage Gap Dataset

Median and Avg Hourly Wages in the USA

Health Insurance Coverage in the USA

Black-White Wage Gap in the USA Dataset

Photo by Canonicalized

Coronavirus affects some members of the population more than others. Emerging evidence suggests that older people, men, people with health conditions such as respiratory and pulmonary conditions, and people of a Black, Asian Minority Ethnic (BAME) background are at particular risk. There are also a number of other wider public health risk factors that have been found to increase the likelihood of an individual contracting coronavirus. This briefing presents descriptive evidence on a range of these factors, seeking to understand at a London-wide level the proportion of the population affected by each.

Dataset population: Persons

Country of birth

Country of birth is the country in which a person was born. This topic records whether the person was born in or if they were not born in a country.

For the full country of birth classification in England and Wales, please see the National Statistics Country Classification.

Ethnic group

Ethnic group classifies people according to their own perceived ethnic group and cultural background.

This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the 'Irish' response category. This topic was created as part of the commissioned table processing.

The "Enslaved People in the African American National Biography, 1508-1865" dataset builds on the complete print and online collection of the African American National Biography (AANB), edited by Henry Louis Gates, Jr. and Evelyn Brooks Higginbotham. The full collection contains over 6,000 biographical entries of named historical individuals, including 1,304 for subjects born before 1865 and the abolition of slavery in the United States. In making a subset of biographical entries from the multivolume work, the goal was to extract life details from those biographies into an easy-to-view database form that details whether a subject was enslaved for some or all of their lives and to provide the main biographical details of each subject for contextual analysis and comparison. 52 fields covering location data; gender; names, alternate names and suffixes; dates and places of birth and death; and up to 8 occupations were included. We also added 13 unique fields that provide biographical details on each subject: Free born in North America; Free before 13th Amendment; Ever Enslaved; How was freedom attained; Other/uncertain status; African born; Parent information; Runaways and rebels; Education/literacy; Religion; Slave narrative or memoir author; Notes; and Images.

Indicator : PopulationTheme: PeopleSource : Office for National Statistics - Population Estimates - local authority basedFrequency : AnnualDefinition : Estimates of usual resident population by local authority covering the period up to 30 June in the recorded year. Usual resident population refers to people who reside for 12 months or more. This dataset shows annual population estimates in the Black Country area by local authority, showing population by age and gender between 2011-2023.Latest Period : 2023Released : 2024Next Update : 2025Link: https://www.nomisweb.co.uk/

About the Dataset:

Amazon is one of the biggest online retailers in the USA that sells over 12 million products. With this dataset, you can get an in-depth idea of what products sell best, which SEO titles generate the most sales, the best price range for a product in a given category, and much more.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

Similar datasets:

Amazon UK Products

Amazon Canada Products

Amazon India Products

Interesting Task Ideas:

1. Uncover trending product categories and their sales performance.
2. Analyze customer ratings to find top-rated products.
3. Train a product title generator that can generate sales-worthy product titles based on products with the most sales.
4. Gain insight into the best price for any given product based on sales data and competition.
5. Identify which niches are the easiest to make sales in.
6. Gain insights into the general spending habits of online shoppers.
7. Use as a seed dataset for practicing database management and performance optimization.
8. Train (or learn to train) an AI-based search model to recommend Amazon products.

Checkout my other datasets

USA Unemployment Rates by Demographics & Race

USA Hispanic-White Wage Gap Dataset

Median and Avg Hourly Wages in the USA

Health Insurance Coverage in the USA

Black-White Wage Gap in the USA Dataset

Unequal impact of COVID-19: BAME disproportionality This slide pack covers lived experience from schools and the voluntary sector covering a number of emerging issues arising from our schools relating to disadvantaged children and families, which can often be attributed to the experiences of our Black, Asian and other or mixed ethnicity communities. Data covers opportunities for Black, Asian and other or mixed ethnicity graduates from a Carnegie UK Trust report. It also covers first hand experiences of young people through roundtable discussions with a group of young people including Camden’s Youth MPs joined by Cllr Georgia Gould and Sir Keir Starmer MP.

This dataset provides Census 2021 estimates that classify usual residents in Northern Ireland by ethnic group.

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.

This table reports the categories for which there are 10 or more usual residents. Where there are fewer than 10 usual residents for any category, these have been reported in a residual group which may or may not contain 10 or more usual residents in total.

All ethnic groups are classified within one of the five groups: White, Asian, Black, Mixed, and Other. 'Irish Traveller' is included in 'Other'; this is changed from Census 2011 when 'Irish Traveller' was included in 'White'.

Quality assurance report can be found here

Dataset population: Persons

Age

Age is derived from the date of birth question and is a person's age at their last birthday, at 27 March 2011. Dates of birth that imply an age over 115 are treated as invalid and the person's age is imputed. Infants less than one year old are classified as 0 years of age.

Ethnic group

Ethnic group classifies people according to their own perceived ethnic group and cultural background.

This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the 'Irish' response category. This topic was created as part of the commissioned table processing.

General health

General health is a self-assessment of a person's general state of health. People were asked to assess whether their health was very good, good, fair, bad or very bad.

For England and Wales, this assessment is not based on a person's health over any specified period of time.

For Northern Ireland, 'General health' refers to a person's health over the 12 months prior to Census day (27 March 2011).

Sex

The classification of a person as either male or female.

Description

This data companion pack is a resource intended to frame and be read alongside the linked Evidence Review: Housing and Health Inequalities in London (available on the Institute of Health Equity website) .

The resource provides intelligence and context on the housing and health inequalities in London only, while the accompanying rapid review of evidence for interventions contains the recommendations for action.​

1. This pack is intended to provide a high-level overview of the best available data on housing in London and the key housing-related health inequalities issues faced by Londoners, in correlation with the IHE Evidence Review: Housing and Health Inequalities in London.​
2. This pack identifies how certain groups in the population are at greatest risk of housing-related health inequalities, as well as noting gaps in available data for particularly excluded groups.
3. The pack provides a platform for partnership work on housing-related health inequalities across London, including providing an overview of key issues, and identifying key gaps in intelligence that would help improve understanding of housing-related inequalities across the capital. ​

Audience

It will be useful for health leaders, analysts, officers, and policy makers from local and regional government, integrated care systems, and more, to address ​housing-related health inequalities by -

• Advocating for the need for action to address housing inequalities, given impacts on health and health inequalities ​
• Framing the context for the interventions highlighted in the linked rapid review of interventions​
• Engaging communities ​

​Development of this resource

The Institute of Health Equity (IHE), Greater London Authority (GLA) Health, GLA City Intelligence Unit, Office for Health Improvement and Disparities London (OHID), Association of Directors of Public Health London (ADPH), and NHSE have collaboratively produced this report, as part of the Building the Evidence (BTE) programme of work

• The sources of data available and topics included have been identified from existing published data, working in partnership through iterative discussion
• The resource is provided in PDF and PowerPoint format to support colleagues in their work to
• There is no current plan for periodic updates of this resource, though this will be discussed on completion of this programme of work

Other useful resources:

• The Integrated Care Systems (ICS) Housing Profile is a resource that aims to support people working in ICSs and ICBs to understand, and work jointly with partners to mitigate and tackle the key housing-related issues that drive poor health in London.