Neidio i'r cynnwys
Welsh Government
Darparwr data: Llywodraeth Cymru Ystadegau Arbrofol Ethnigrwydd yn ôl Oedran a Rhyw
None
Mesur[Hidlwyd]
Blwyddyn[Hidlwyd]
Measure2
[Lleihau]Ethnigrwydd[Hidlo]
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Ethnigrwydd 1
[Lleihau]Rhyw[Hidlo]
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Rhyw 1
[Lleihau]Oedran[Hidlo]
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Oedran 1
[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm
[Lleihau]Gwyn[Lleihau]Grwpiau ethnig cymysg/lluosog[Lleihau]Asiaidd[Lleihau]Du / Affricanaidd / Caribïaidd / Du Prydeinig[Lleihau]Grwpiau ethnig eraill
[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm[Lleihau]CyfanswmCliciwch yma i ddidoliCyfanswm
Cliciwch yma i ddidoliBenywaiddCliciwch yma i ddidoliGwrywaiddCliciwch yma i ddidoliBenywaiddCliciwch yma i ddidoliGwrywaiddCliciwch yma i ddidoliBenywaiddCliciwch yma i ddidoliGwrywaiddCliciwch yma i ddidoliBenywaiddCliciwch yma i ddidoliGwrywaiddCliciwch yma i ddidoliBenywaiddCliciwch yma i ddidoliGwrywaidd
[Lleihau]Cyfanswm1,493,7001,460,2002,953,800(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.14,600(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.14,900(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.29,500(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.38,100(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.33,400(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.71,500(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.13,900(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.13,500(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.27,400(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.11,600(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.13,600(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.25,2003,110,000
Cyfanswm0-15 oed250,200260,600510,800(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.7,300(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.8,500(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.15,900(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.10,100(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.10,400(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.20,500(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.4,300*The data item is disclosive or not sufficiently robust for publication(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.8,500*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.7,600564,300
16-64 oed905,200905,8001,811,000(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.7,100(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.6,000(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.13,100(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.26,800(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.21,300(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.48,000(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.9,200(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.8,100(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.17,300(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.8,000(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.8,400(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.16,4001,906,900
65+ oed338,200293,800632,100*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication*The data item is disclosive or not sufficiently robust for publication638,800

Metadata

Disgrifiad cyffredinol

Mae'r tabl hwn yn cyflwyno data ar bob person yng Nghymru.

Casgliad data a dull cyfrifo

Mae'r data yn seiliedig ar ddadansoddiad Llywodraeth Cymru o setiau data Arolwg Poblogaeth Flynyddol a ddarperir gan y Swyddfa Ystadegau Gwladol.

Amlder cyhoeddi

Blynyddol

Cyfnodau data dan sylw

Mae'r ffigurau a ddangosir yn ymwneud â cyfartaleddau aml-flwyddyn, fel nodwyd

Talgrynnu wedi'u ddefnyddio

Mae'r ffigurau wedi'u talgrynnu i'r 100 agosaf ac felly mae'n bosibl y bydd rhai mân anghysondebau ymddangosiadol rhwng swm yr eitemau sy'n rhan ohonynt a'r cyfansymiau fel y'u dangosir.

Teitl

Arolwg Poblogaeth Blynyddol: Ethnigrwydd

Diweddariad diwethaf

Ionawr 2022 Ionawr 2022

Diweddariad nesaf

Tachwedd 2022

Sefydliad cyhoeddi

Llywodraeth Cymru

Ffynhonnell 1

Arolwg Blynyddol o’r Boblogaeth, y Swyddfa Ystadegau Gwladol

Cyswllt ebost

ystadegau.cynhwysiant@llyw.cymru

Dynodiad

Ystadegau arbrofol

Lefel isaf o ddadelfennu daearyddol

Cymru

Cwmpas daearyddol

Cymru

Cwmpas ieithyddol

Saesneg a Chymraeg

Trwyddedu data

Gallwch ddefnyddio ac ailddefnyddio'r data hwn am ddim mewn unrhyw fformat neu gyfrwng, dan delerau'r Drwydded Llywodraeth Agored - gweler http://www.nationalarchives.gov.uk/doc/open-government-licence-cymraeg

Ansawdd ystadegol

Mae ymatebion i’r Arolwg Poblogaeth Blynyddol (APS) yn cael eu pwysoli i ragamcaniadau poblogaeth swyddogol. Roedd y rhagamcaniadau ar gyfer 2020 yn seiliedig ar 2018, ac, felly, roeddent yn seiliedig ar dueddiadau demograffig a oedd yn rhagddyddio’r pandemig COVID-19. Er mwyn caniatáu ar gyfer gwahanol dueddiadau yn ystod y pandemig, mae'r ymatebion ar gyfer yr APS wedi'u hail-bwysoli ar 9 Medi 2021 i boblogaethau newydd sy'n deillio o gyfraddau twf o Wybodaeth Amser Real (RTI) o Refeniw a Thollau EM (HMRC). Mae'r ail-bwysoli wedi'i gymhwyso o'r flwyddyn data sy’n diweddu Mawrth 2020 ymlaen ac mae'n rhoi amcangyfrifon gwell o'r cyfraddau a'r lefelau. Dylai'r newidiadau mae'r SYG wedi'u gwneud i'r pwysoli leihau gogwydd yr amcangyfrifon ar lefelau uchel o gyfanrediadau. Efallai y bydd rhai dadansoddiadau llai yn cael eu heffeithio'n negyddol a gellir gweld newidiadau mwy eithafol o ystyried maint llai y sampl sylfaenol ers dechrau'r pandemig.

Gan fod y data yn dod o arolwg, mae’r canlyniadau yn amcangyfrifon sy’n seiliedig ar sampl ac felly yn ddarostyngedig i wahanol raddau o amrywioldeb samplu, h.y. mae’r gwir werth unrhyw fesur yn gorwedd mewn amrywiaeth gwahanol am y gwerth a amcangyfrifwyd. Mae’r amrediad neu amrywioldeb samplu yn cynyddu wrth i'r manylder yn y data gynyddu, er enghraifft mae data awdurdodau lleol yn destun i amrywioldeb uwch na data rhanbarthol.

Allweddeiriau

Ethnigrwydd; Cydraddoldeb ac Amrywiaeth

Enw

EQU1030