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License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Victoria County. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Victoria County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 61.59% of the total residents in Victoria County. Notably, the median household income for White households is $71,917. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $146,591. This reveals that, while Whites may be the most numerous in Victoria County, Asian households experience greater economic prosperity in terms of median household income.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Victoria County median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chart and table of population level and growth rate for the Melbourne, Australia metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.
Annual population estimates as of July 1st, by census metropolitan area and census agglomeration, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.
Canada's largest metropolitan area is Toronto, in Ontario. In 2022. Over 6.6 million people were living in the Toronto metropolitan area. Montréal, in Quebec, followed with about 4.4 million inhabitants, while Vancouver, in Britsh Columbia, counted 2.8 million people as of 2022.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Victoria in Future 2016 (VIF2016) is the official state government projection of population and households. Projections are used by decision makers across government and in other areas. The results are driven by assumptions concerning demographic and land use trends. Projections are based on the latest (30 June 2015) population estimates from the Australian Bureau of Statistics (ABS) and incorporate the results of the 2011 Census. For Victoria and major regions, the projections cover the period from 2011 to 2051. For Local Government Areas (LGA) and Victoria in Future Small Areas (VIFSA), the projections extend to 2031.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
澳大利亚 Population: Resident: Estimated: Annual: Victoria: Greater Melbourne在2017达4,843,781.000 人口,相较于2016的4,714,387.000 人口有所增长。澳大利亚 Population: Resident: Estimated: Annual: Victoria: Greater Melbourne数据按每年更新,2006至2017期间平均值为4,217,604.500 人口,共12份观测结果。该数据的历史最高值出现于2017,达4,843,781.000 人口,而历史最低值则出现于2006,为3,760,760.000 人口。CEIC提供的澳大利亚 Population: Resident: Estimated: Annual: Victoria: Greater Melbourne数据处于定期更新的状态,数据来源于Australian Bureau of Statistics,数据归类于Global Database的澳大利亚 – Table AU.G002: Estimated Resident Population。
This summary shows the results of the forecasts for population, households and dwellings in the City of Greater Geelong. The period 2020, 2030 and 2040, as the short to medium term, is likely to be the most accurate and useful forecast information for immediate planning purposes.
It is important to look at the relationship between population and average household size. If the average household size is falling, then there will need to be growth in the number of households (and dwellings for them to live in) to maintain or grow the population.
This chart shows how many individuals can carry a conversation in English only, in French only, in both English and French, or in neither English nor French.
This atlas-style report presents a spatial demographic analysis for Victoria including measures of population vulnerability. It updates the 2016 report which relied on data from the ABS 2011 census of population and housing. This version uses information from the 2016 census along with other updated population data. Key findings include: • Fire is a natural part of the Australian landscape but its incidence and impact can be increased by the presence of people. • Measures of vulnerability are indicative. They do not predict how a particular individual will respond to a specific event. Nevertheless, research studies have shown that some characteristics are associated with an individual’s level of vulnerability before, during, or after a disaster. • Population vulnerabilities have a geographical distribution. Some communities will have a greater measure of vulnerability than others, and some locations may display multiple types of vulnerability. • The vulnerability level of a household will be determined by its weakest rather than its strongest member. KEY FINDINGS • Population characteristics change over time. Hence patterns of vulnerability can also change over time. Sometimes changing characteristics occur because people move into or out of a community. Other changes occur within a population. Children may be born, increasing the number of infants in a community, or people may age in place, causing an increse in numbers of older people. • In Melbourne’s fringe and peri-urban areas, this pattern of ageing in place is likely to cause a significant increase in numbers of older people. • Most population measures are based on where people usually live or work, yet people can be highly mobile. • People may have more than one residence. This can include: holiday homes; weekenders; or for regional populations, a townhouse in the city. • Population mobility presents particular challenges for risk assessment and emergency management. Towns may vary in population size by a factor of four or five during particular seasons of the year. • Popular visitor and holiday locations such as the Dandenong Ranges and Great Ocean Road have particularly high fire risk. Planning for fire therefore requires an understanding of both permanent and part-time populations.
The household incomes chart shows how many household fall in each of the income brackets specified by Statistics Canada.
Ages chart illustrates the age and gender trends across all age and gender groupings. A chart where the the covered area is primarily on the right describes a very young population while a chart where the the covered area is primarily on the left illustrates an aging population.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Ambulance Victoria has two official response time targets: Respond to Code 1 incidents within 15 minutes for 85% of incidents state-wide, and Respond to Code 1 incidents within 15 minutes for 90% of incidents in urban centres with populations greater than 7,500. Response times are an important measure of the service we provide, but are only one of a number of measures used to gauge the effective delivery of an ambulance service. \r Our response times are measured from the receipt of the triple zero (000) call until paramedics arrive on scene. Response times are influenced by many factors including traffic, distance required to travel, availability of ambulances and demand for our services. \r We designate those patients that require urgent paramedic and hospital care as "Code 1", and these patients receive a "lights and sirens" response. The tables provide information about our Code 1 response time performance by both Local Government Area (LGA) and Urban Centres and Localities (UCL). Code 2 incidents are acute, but not time critical and do not require a lights and sirens response. AV's average Code 2 response time performance has also been provided. \r As part of our process of continual improvement, the response time performance shown below has been calculated using data sourced from the Computer Aided Dispatch (CAD) system used across Victoria. UCLs : These are geographical areas based on the Australian Bureau of Statistics Urban Centres and Localities (UCLs) boundaries and residential population. Ambulance Victoria reports performance for larger UCLs where population exceeds 7,500 persons.
The median income indicates the income bracket separating the income earners into two halves of equal size.
This table contains data for gross domestic product (GDP), in current dollars, for all census metropolitan area and non-census metropolitan areas.
Age-sex charts emphasize the gap between the numbers of males and females at a specific age group. It also illustrates the age and gender trends across all age and gender groupings. A chart skewed heavily to the left describes a very young population while a chart skewed heavily to the right illustrates an aging population.
A combination of surveys and experiments were used to determine the size distribution, recruitment, mortality and growth rates of Siphonaria diemenensis in 2 zones on the rocky shore at Griffith Point, San Remo, Victoria. One zone was in the high intertidal (Zone 2) and one was in the low intertidal area on the shore. There were 3 sites in Zone 1 and 2 sites in Zone 2 (see parent record for more details).
A size frequency distribution was constructed for each site from surveys that recorded the size of all individuals every 2 months from October 1979 to December 1981. In addition to the sites in Zone 1 there were 12 permanent quadrats (50 x 50cm) which were surveyed in the same manner from December 1980 to December 1981. The sizes of recruits were similar in both Zones but the sizes of adults were significantly greater in Zone 2. In both years, the maximum density of recruits in Zone 1 was greater than in Zone 2. The mortality rate of adult limpets in Zone 2 was lower compared to limpets in Zone 1.
The growth rates (mm per month) of marked individuals were calculated for 3 time intervals; January-March, March-May and May-late July (Zone 2) and Mary-early August (Zone 1) in 1981. Limpets in Zone 2 grew faster (average 0.63 mm per month) than the limpets in Zone 1 (average 0.11mm per month).
In addition, an experiment was conducted in Zone 1 from May to July in 1981 to determine the effects of adult density and macroalgal cover on limpet recruitment. It was found that there was no effect of adult density but a significant interactive effect of algal cover and sampling date on the number of limpet recruits.
Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2023.
Number of people belonging to a visible minority group as defined by the Employment Equity Act and, if so, the visible minority group to which the person belongs. The Employment Equity Act defines visible minorities as 'persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour.' The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Victoria County. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Victoria County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 61.59% of the total residents in Victoria County. Notably, the median household income for White households is $71,917. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $146,591. This reveals that, while Whites may be the most numerous in Victoria County, Asian households experience greater economic prosperity in terms of median household income.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Victoria County median household income by race. You can refer the same here