Introduction

Google Fit Statistics: Google Fit, since its launch in 2014, formed the major platform of fitness and health for Google, enabling users to track several health metrics and pool data from several fitness apps and devices. In its continued evolution were added unique features like Heart Points, developed under the auspices of WHO and AHA, aimed at inducing physical activity.

Changes of much significance are due in 2024, marking a change in Google's very own approach to health data-keeping. In this article, we will enclose the Google Fit statistics.

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-59, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Cellule de Planification et de Statistiques (CPS/SSDSPF), Institut National de la Statistique (INSTAT), Centre d’Études et d’Information Statistiques (INFO-STAT) [Mali] and ICF International.

SAMPLE UNIT: Women SAMPLE SIZE: 10424

SAMPLE UNIT: Birth SAMPLE SIZE: 33803

SAMPLE UNIT: Child SAMPLE SIZE: 10326

SAMPLE UNIT: Man SAMPLE SIZE: 4399

SAMPLE UNIT: Member SAMPLE SIZE: 58330

Mode of data collection

Face-to-face [f2f]

Introduction

Social Media Marketing Statistics: Social media marketing is a key part of any digital marketing plan today. With over 50% of the world’s population using social media, brands need to be active on these platforms. But it’s not just about making profiles and posting content. Effective social media marketing involves keeping up with changing algorithms and trends and understanding the behaviors of your target audience. Social media’s interactive and engaging nature helps businesses connect with their audience in ways they couldn’t before.

This opens up new opportunities for engaging with people, building the brand, and doing direct marketing. We shall shed more light on Social Media Marketing Statistics through this article.

Per Industry (NACE Rev.2) : Gross value added (Current prices and volumes) (in millions EUR) Compensation of employees (Current prices) (in millions EUR) Employment : Persons (in 1 000 persons) Employment : hours (in 1000 hours worked) Description copied from catalog.inspire.geoportail.lu.

Données statistiques issues du logiciel de billetterie du musée : nombre de visiteurs par catégorie tarifaire. Période concernée : 01/08/2018 au 31/08/2018

RCS - Statistiques des immatriculations en 2018

Introduction

PayPal Statistics: Paypal is a multinational American company focusing on online payments and money transfers. It was developed to serve as an alternative to traditional cash payments and money orders. The company has evolved to become a popular payment platform. As we go forward, we will learn about PayPal Statistics to garner a better understanding of relevant statistical data and gain essential information about the factors that have led to the growth of this company altogether. By the end of this, people can learn about the development of the online payment business.

Ce jeu de données, validé par la commission des mouvements de population, donne l'historique des PDIs (Personnes Déplacées Internes) et Réfugiés par sous-préfecture.

Il s’agit du nombre d’élèves inscrits dans le niveau primaire d’un établissement d’enseignement (de la Fédération Wallonie-Bruxelles, de la Communauté germanophone ou de la Communauté flamande) localisé dans la commune, quelle que soit leur commune de domicile (y compris les élèves domiciliés à Bruxelles, en Flandre ou à l’étranger). http://walstat.iweps.be/fichiers/metadonnees/meta-243200.pdf

Gross operating surplus and mixed income of non-financial corporations (in EUR) Net lending/net borrowing of non-financial and financial corporations (in EUR) Description copied from catalog.inspire.geoportail.lu.

Aperçu: Chaque trimestre, le Programme des travailleurs étrangers temporaires (PTET) publie des statistiques sur l’évaluation d’impact sur le marché du travail (EIMT) sur le portail de données ouvertes du gouvernement, y compris des données trimestrielles et annuelles sur l'EIMT concernant, mais sans s'y limiter, les postes de TET demandés et approuvés, le lieu d’emploi, les professions, les secteurs, le volet du programme des TET, et les travailleurs étrangers temporaires par pays d'origine. Le PTET ne recueille pas de données sur le nombre de TET qui qui ont été embauchés par un employeur et qui sont arrivés au Canada. La décision de délivrer un permis de travail appartient à Immigration, Réfugiés et Citoyenneté Canada (IRCC) et une poste dont l'EIMT est positive ne donnent pas toujours lieu à la délivrance d'un permis de travail. Pour ces raisons, les données fournies dans les statistiques de l'EIMT ne peuvent pas être utilisées pour calculer le nombre de TET qui sont entrés ou entreront au Canada. IRCC publie des statistiques annuelles sur le nombre de travailleurs étrangers qui ont obtenu un permis de travail : https://open.canada.ca/data/fr/dataset/360024f2-17e9-4558-bfc1-3616485d65b9. Veuillez noter que tous les tableaux trimestriels ont été mis à jour pour la CNP 2021 (5 chiffres et en fonction de la formation, des études, de l’expérience et des responsabilités (FEER)). Ainsi, les tableau 5, 8, 17 et 24 ne seront plus mis à jour mais resteront des tableau archivés. Fréquence de publication: Les statistiques trimestrielles de l'EIMT couvrent les données des quatre trimestres de l'année civile précédente et le(s) trimestre(s) de l'année civile en cours. Les données trimestrielles sont publiées dans les deux à trois mois suivant le trimestre le plus récent. Les dates de publication des données trimestrielles sont les suivantes : Le premier trimestre (janvier à mars) sera publié au début du mois de juin de l'année en cours ; le deuxième trimestre (avril à juin) sera publié au début du mois de septembre de l'année en cours ; le troisième trimestre (juillet à septembre) sera publié au début du mois de décembre de l'année en cours ; et le quatrième trimestre (octobre à décembre) sera publié au début du mois de mars de l'année suivante. Les statistiques annuelles couvrent huit années consécutives de données relatives à l'EIMT et devraient être publiées en mars de l'année suivante. Les données publiées: Dans le cadre de la publication trimestrielle, le PTET met à jour les données de l'EIMT pour 28 tableaux ventilés selon les catégories suivantes : Les postes de TET : Tables 1 à 10, 12, 13, et 22 à 24; Les demandes d’EIMT : Tables 14 à 18; Les employeurs : Tables 11, et 19 à 21; La Programme des travailleurs agricoles saisonniers (PTAS) : Tables 25 à 28. De plus, le PTET publie 2 listes d'employeurs ayant reçu une EIMT positive ou négative : les employeurs qui ont reçu une EIMT positive par volet de programme, CNP et lieu d'affaires (https://open.canada.ca/data/fr/dataset/90fed587-1364-4f33-a9ee-208181dc0b97/resource/b369ae20-0c7e-4d10-93ca-07c86c91e6fe); et les employeurs qui ont reçu une EIMT négative par volet de programme, CNP et lieu d'affaires (https://open.canada.ca/data/fr/dataset/f82f66f2-a22b-4511-bccf-e1d74db39ae5/resource/94a0dbee-e9d9-4492-ab52-07f0f0fb255b) Les éléments importants à ne pas oublier : 1. Lorsque des données sont présentées sur des EIMT positives ou négatives, la date de décision est utilisée pour déterminer le trimestre auquel les données appartiennent. Cependant, lorsque les données sont présentées sur la date où les EIMT sont demandées, elles sont basées sur la date à laquelle l'EIMT est reçue par EDSC. 2. À compter de la publication des données du 2022Q1-2023Q4 (publié en avril 2024) et aller de l’avant, toutes les EIMT à l'appui de la " résidence permanente (RP) seulement " sont incluses dans les statistiques du PTET, sauf indication contraire. Toutes les données trimestrielles de ce rapport incluent les EIMT de la RP uniquement. Les EIMT à double intention et les postes correspondants sont inclus dans leur volet respectif du PTET (p. ex., bas salaire, haut salaire, etc.), ce qui peut avoir une incidence sur les rapports du programme au fil du temps. 3. Une attention particulière doit être portée aux données présentées par des « employeurs uniques » lorsqu'il s'agit de manipuler les données dans ce tableau spécifique. Un employeur peut être compté dans plusieurs groupes s'il a plusieurs EIMT positives dans des catégories comme le volet du programme, la province ou le territoire, ou la région économique. Par exemple, un employeur pourrait demander des travailleurs étrangers temporaires pour deux lieux de travail différents, et cet employeur serait inclus dans les statistiques des deux régions économiques. De plus, en tant que tel, la somme des lignes de ces tableaux « Employeur unique » ne correspondra pas au total global.

Inpatient Statistics (i) Inpatient Discharges and Deaths in All Hospitals Classified by Disease, 2023 (ii) Inpatient Discharges and Deaths in Hospitals and Registered Deaths in Hong Kong by Disease, 2023

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

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The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).

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The variables for part 1 of the dataset are:

• Census usually resident population count
• Census night population count
• Age (5-year groups)
• Age (life cycle groups)
• Median age
• Birthplace (NZ born/overseas born)
• Birthplace (broad geographic areas)
• Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’
• Māori descent indicator
• Languages spoken (total responses)
• Official language indicator
• Gender
• Cisgender and transgender status – census usually resident population count aged 15 years and over
• Sex at birth
• Rainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and over
• Sexual identity for the census usually resident population count aged 15 years and over
• Legally registered relationship status for the census usually resident population count aged 15 years and over
• Partnership status in current relationship for the census usually resident population count aged 15 years and over
• Number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Average number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Religious affiliation (total responses)
• Cigarette smoking behaviour for the census usually resident population count aged 15 years and over
• Disability indicator for the census usually resident population count aged 5 years and over
• Difficulty communicating for the census usually resident population count aged 5 years and over
• Difficulty hearing for the census usually resident population count aged 5 years and over
• Difficulty remembering or concentrating for the census usually resident population count aged 5 years and over
• Difficulty seeing for the census usually resident population count aged 5 years and over
• Difficulty walking for the census usually resident population count aged 5 years and over
• Difficulty washing for the census usually resident population count aged 5 years and over.

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Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.

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Symbol

-997 Not available

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

The archival documents of the heritage libraries of the City of Paris have been digitised and continue to be digitised. Drawings, prints, commercial catalogues, exhibitions, postcards but also 78 tours are available for consultation on the portal of specialised libraries. The statistical table lists the + 1 million images per document type.

Description: Tax statistics of income subject to personal income tax by statistical sector Period: 2005-2018 Source: https://statbel.fgov.be/fr/open-data/statistique-fiscale-des-revenus-par-secteur-statistique

Turkey Vital Statistics: Dependency Ratio data was reported at 47.245 NA in 2017. This records an increase from the previous number of 47.158 NA for 2016. Turkey Vital Statistics: Dependency Ratio data is updated yearly, averaging 48.030 NA from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 50.360 NA in 2007 and a record low of 47.158 NA in 2016. Turkey Vital Statistics: Dependency Ratio data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.G003: Vital Statistics.

To help you get the biggest takeaways from all of these digital marketing stats, I want to share some trends in marketing that’s working for businesses right now.

About this dataset

Context

The dataset tabulates the population of Munich by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Munich. The dataset can be utilized to understand the population distribution of Munich by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Munich. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Munich.

Key observations

Largest age group (population): Male # 25-29 years (42) | Female # 55-59 years (35). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Munich population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Munich is shown in the following column.
• Population (Female): The female population in the Munich is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Munich for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Munich Population by Gender. You can refer the same here

Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.