Chart and table of population level and growth rate for the Cape Town, South Africa metro area from 1950 to 2025.

About this dataset

Context

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

Key observations

The percent distribution of Cape Vincent town population by race (across all racial categories recognized by the U.S. Census Bureau): 77.08% are white, 11.54% are Black or African American, 0.55% are American Indian and Alaska Native, 1.10% are Asian, 3.31% are some other race and 6.42% 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 Cape Vincent town
• Population: The population of the racial category (excluding ethnicity) in the Cape Vincent town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Cape Vincent town 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 Cape Vincent town Population by Race & Ethnicity. You can refer the same here

As of 2024, South Africa's population increased, counting approximately 63 million inhabitants. Of these, roughly 27.5 million were aged 0-24, while 654,000 people were 80 years or older. Gauteng and Cape Town are the most populated South Africa’s yearly population growth has been fluctuating since 2013, with the growth rate dropping below the world average in 2024. The majority of people lived in the borders of Gauteng, the smallest of the nine provinces in terms of land area. The number of people residing there amounted to 16.6 million in 2023. Although the Western Cape was the third-largest province, the city of Cape Town had the highest number of inhabitants in the country, at 3.4 million. An underemployed younger population South Africa has a large population under 14, who will be looking for job opportunities in the future. However, the country's labor market has had difficulty integrating these youngsters. Specifically, as of the fourth quarter of 2024, the unemployment rate reached close to 60 percent and 384 percent among people aged 15-24 and 25–34 years, respectively. In the same period, some 27 percent of the individuals between 15 and 24 years were economically active, while the labor force participation rate was higher among people aged 25 to 34, at 74.3 percent.

About this dataset

Context

The dataset tabulates the Cape Vincent town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Cape Vincent town. The dataset can be utilized to understand the population distribution of Cape Vincent town by age. For example, using this dataset, we can identify the largest age group in Cape Vincent town.

Key observations

The largest age group in Cape Vincent Town, New York was for the group of age 30 to 34 years years with a population of 274 (10.79%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Cape Vincent Town, New York was the 85 years and over years with a population of 54 (2.13%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Cape Vincent town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Cape Vincent town 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 Cape Vincent town Population by Age. You can refer the same here

South Africa is the sixth African country with the largest population, counting approximately 60.5 million individuals as of 2021. In 2023, the largest city in South Africa was Cape Town. The capital of Western Cape counted 3.4 million inhabitants, whereas South Africa's second largest city was Durban (eThekwini Municipality), with 3.1 million inhabitants. Note that when observing the number of inhabitants by municipality, Johannesburg is counted as largest city/municipality of South Africa.

From four provinces to nine provinces

Before Nelson Mandela became president in 1994, the country had four provinces, Cape of Good Hope, Natal, Orange Free State, and Transvaal and 10 “homelands” (also called Bantustans). The four larger regions were for the white population while the homelands for its black population. This system was dismantled following the new constitution of South Africa in 1996 and reorganized into nine provinces. Currently, Gauteng is the most populated province with around 15.9 million people residing there, followed by KwaZulu-Natal with 11.68 million inhabiting the province. As of 2022, Black African individuals were almost 81 percent of the total population in the country, while colored citizens followed amounting to around 5.34 million.

A diverse population

Although the majority of South Africans are identified as Black, the country’s population is far from homogenous, with different ethnic groups usually residing in the different “homelands”. This can be recognizable through the various languages used to communicate between the household members and externally. IsiZulu was the most common language of the nation with around a quarter of the population using it in- and outside of households. IsiXhosa and Afrikaans ranked second and third with roughly 15 percent and 12 percent, respectively.

Graph and download economic data for Population Estimate, Total, Hispanic or Latino, Two or More Races (5-year estimate) in Cape May County, NJ (B03002019E034009) from 2009 to 2023 about Cape May County, NJ; Ocean City; NJ; latino; hispanic; estimate; persons; 5-year; population; and USA.

About this dataset

Context

The dataset tabulates the Cape Vincent town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Cape Vincent town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Cape Vincent town was 2,526, a 4.21% increase year-by-year from 2022. Previously, in 2022, Cape Vincent town population was 2,424, a decline of 0.86% compared to a population of 2,445 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cape Vincent town decreased by 805. In this period, the peak population was 3,331 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Cape Vincent town is shown in this column.
• Year on Year Change: This column displays the change in Cape Vincent town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Cape Vincent town Population by Year. You can refer the same here

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

2021 Ethekwini Metro Male and Female Population Demographics Estimates by Stats SA

Abstract

A tender was posted, by the Cape Town City Council, in November 2005 for a socio-economic survey and two focus groups to be conducted in both Khayelitsha and Mitchell's Plain. This tender was awarded to the Unit for Religion and Development at the University of Stellenbosch. The purpose was to update the 2001 Census information as well as to identify key priority issues and needs to inform integrated planning for the areas. In addition, the survey was intended to assess the impact of the Urban Renewal Programme in the respective communities. The objectives of the survey and focus groups were as follows:

• To evaluate the Urban Renewal Programme in the nodes of Khayelitsha and Mitchell’s Plain in order to improve the programme outcomes and the communication thereof;

• To develop a demographic and socio-economic profile of the community in terms of household size and composition, education, income and work status. A socio-economic and demographic profile is important in the identification of community needs to inform planning;

• To measure the communities’ perceptions on the value and importance of various services as well as their level of satisfaction with the delivery of these and other services;

• To identify the key needs of the respective communities in order to inform the City on appropriate investment in facilities, infrastructure and services.

Geographic coverage

Two renewal nodes in the Western Cape: Khayelitsha and Mitchell's Plain

Analysis unit

Households and individuals

Universe

All households and de jure household members within Khayelitsha or Mitchell's Plain.

Kind of data

Sample survey data

Sampling procedure

The survey is a stratified sample of 1 000 households from the study area. The sample was stratified on two levels: first, according to the number of households of the two geographical areas in the study area; and second, according to the number of formal and informal dwelling units in each geographical area (Mitchell’s Plain and Khayelitsha).

Regarding the first level of stratification by the number of households for each nodal area, a sample was selected totalling 453 households for the Mitchell’s Plain area and 547 for Khayelitsha. The second level of stratification by dwelling unit type was done within each nodal area, for Mitchell’s Plain totalling 12 informal dwelling units and 441 formal dwelling units, and for Khayelitsha totalling 311 informal dwelling units and 236 formal dwelling units. Formal and informal households were randomly selected from a small area layer (SAL) data set. This data set was created by combining all enumerated areas (EAs) with a population of less than 500 with adjacent EAs within the same sub-place by Statistics South Africa. Assigned to the SAL are the elected datasets from the 2001 Census, one of which is housing type. Because of the small sample size, comparison between geographic areas and/or different dwelling units within the areas may not be statistically significant.

Mode of data collection

Face-to-face [f2f]

Graph and download economic data for Population Estimate, Total, Hispanic or Latino, American Indian and Alaska Native Alone (5-year estimate) in Cape May County, NJ (B03002015E034009) from 2009 to 2023 about Cape May County, NJ; Ocean City; AK; NJ; American Indian; latino; hispanic; estimate; persons; 5-year; population; and USA.

Abstract

In the year 2000 a small team of social scientists from the Universities of Cape Town and Michigan collaborated on designing a survey with a special focus on labour market issues as a precursor to a Cape Area Panel Study with a special focus on youth planned for the year 2002. After much debate and taking due cognisance of time and budget constraints the team decided to target the magisterial district of Mitchell’s Plain within the Cape Metropole for the survey.

This decision was informed by data gleaned from the 1996 census which revealed that Mitchell’s Plain – demarcated a magisterial district in 1986 – contained almost thirty percent of the population in the Cape Metropolitan Council area. It straddled the two cities of Cape Town and Tygerberg and housed nearly 74% of the African and over 20% of the ‘coloured’ metropolitan population. It included the three established African townships of Langa, Gugulethu and Nyanga as well as informal settlements such as Crossroads and Browns Farm. It also included Khayelitsha an African township proclaimed in the early 1980s with the first houses being built in 1986. The 1996 census had recorded high unemployment rates of over 44%, for Africans and over 20% for Coloured people.

Geographic coverage

The survey covers the Khayelitsha and Mitchell's Plain areas of Cape Town, South Africa.

Analysis unit

The unit of analysis for this survey includes households and individuals.

Universe

The survey covers the African and Coloured populations of the Khayelitsha and Mitchell's Plain areas of Cape Town.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to represent all adults (18 years of age and older) in the Mitchell’s Plain Magisterial district. As discussed above, the most cost-efficient method of interviewing residents of such a large area is to use a two-stage cluster sample. The first stage of this sample entails selecting clusters of households and the second stage entails the selection of the households themselves. For our clusters of households, we relied on the Enumerator Areas as defined by Statistics South Africa for the 1996 Population Census. These Enumerator Areas are neighbourhoods of roughly 50 to 200 households. They are drawn up by the Chief Directorate of Demography at Statistics South Africa. This directorate is responsible for developing and maintaining a GIS system that provides the maps that are used for conducting the five-yearly national population census (Statistics South Africa, 2001:42-44). Although Enumerator Area boundaries do not cross municipal boundaries, they do not correspond to any other administrative demarcations such as voting wards. Enumerator Areas are designed to be homogeneous with respect to housing type and size. For example, Enumerator Area boundaries within the Mitchell’s Plain Magisterial District do not usually cut across different types of settlements such as squatter camps, site and service settlements, hostels, formal council estates or privately built estates. Instead, each Enumerator Area is homogeneous with respect to any one of these housing types.

The method of selection used was that of Probability Proportional to Size (PPS). The measure of size being the number of households in each Enumerator Area as measured by the 1996 Population Census. This method was chosen as it provides the most efficient way to obtain equal subsample sizes across two stages of selection, i.e. we are able to select the Enumerator Areas and then select from each Enumerator Area a constant number of households for all Enumerator Areas in the sample. The sample is implicitly stratified by location and by housing type.

A more detailed description of the sampling method and procedure for this survey can be found in the sampling method document available through this site under Other Study Materials.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household questionnaire: Was aimed at establishing the household roster with the usual questions on age, gender and relationships. It was divided into two sections covering those aged 18 and older and those younger than 18. For the latter a separate set of questions covering education, health and work status was included.

The adult questionnaire: Was aimed to fit the international standard approach on the labour force by allocating the labour market status of ‘employee’ to all those ‘at work’ (for profit or family gain, in cash or in kind). One of the innovative aspects of the survey was that respondents were asked about all income-earning activities. In other words, they were not allocated into particular labour market categories during the process of the interview.

The adult questionnaire was divided into 13 sections:

• Section A on education and other characteristics covered age, racial classification, educational attainment, language, religion and health. • Section B on migration covered place of origin, relocation and destination. • Section C on intergenerational mobility aimed at capturing parental influence on the respondent. • Section D on employment history aimed at capturing the respondent’s work history. • Section E on wage employment attempted to capture respondents working for a wage or salary whether full-time, part-time, in the formal sector or the informal sector including those who had more than one job. • Section F on unemployment included questions on job search • Section G on self-employment included a question on more than one economic activity and the frequency of self-employment. • Section H on non-labour force participants was aimed at refining work status. • Section I on casual work aimed to capture not only those in irregular/short term employment but also people who might have more than one job. • Section J on helping other people with their business for gain was aimed at identifying respondents who assist others from time to time but who might not regard themselves as ‘working’. • Section K on reservation wages attempted to establish the lowest wage at which a respondent would accept work. • Section L on savings, borrowing and grants and investment income attempted to capture income derived from sources other than work • Section M on perceptions of distributive justice posed a number of attitudinal questions.

Graph and download economic data for Resident Population in Cape May County, NJ (NJCAPE1POP) from 1970 to 2024 about Cape May County, NJ; Ocean City; NJ; residents; population; and USA.

As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Cape Vincent town by race. It includes the distribution of the Non-Hispanic population of Cape Vincent town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Cape Vincent town across relevant racial categories.

Key observations

Of the Non-Hispanic population in Cape Vincent town, the largest racial group is White alone with a population of 1,957 (82.64% of the total Non-Hispanic population).

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 (for Non-Hispanic) for the Cape Vincent town
• Population: The population of the racial category (for Non-Hispanic) in the Cape Vincent town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Cape Vincent town total Non-Hispanic 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 Cape Vincent town Population by Race & Ethnicity. You can refer the same here

U.S. Census Bureau QuickFacts statistics for Cape Elizabeth town, Cumberland County, Maine. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Large carnivores play a vital role in structuring our ecosystems, yet they face mounting threats such as habitat loss, prey reduction and persecution. These threats reduce their global distribution and impacts their population numbers. Protected areas can offer refuge for large carnivores, however leopards (Panthera pardus), can persist outside of these areas and often occupy mixed-use landscapes. Our understanding of how leopards persist over time in mixed-use landscapes is limited, especially in the semi-arid regions of southern Africa. This study, to the best of my knowledge, is the only multi-session maximum likelihood spatial capture-recapture (SCR) analysis to have been conducted in a semi-arid environment outside of a protected area in Southern Africa. The study aimed to estimate leopard population changes over time and to investigate the possible drivers affecting density, using three surveys (2012, 2017, 2022), in the mixed-use landscape of the Little Karoo in the Western Cape, South Africa. In 2012, a total of 141 paired camera stations were used for a total of 13,050 trap days resulting in 29 unique leopard captures. In 2017, a total of 40 paired camera stations were used for a total of 2,128 trap days resulting in 18 unique leopard captures and in 2022 a total of 64 paired camera stations were used for a total of 8,997 trap days resulting in 37 unique leopard captures. The best performing density model indicated an increasing population trend over the study period which included a trend term on density (D~year) and an interaction term (individual session*sex) on λ0 (capture rate) and σ (spatial decay). Density estimates (Standard Error) for leopard populations for the three surveys 2012, 2017, and 2022, were 0.52 (± 0.11), 0.70 (± 0.08), and 0.95 (± 0.08) leopards per 100 km2, respectively. Terrain ruggedness, elevation, vegetation type and distance from major rivers were all important drivers in leopard density in the Little Karoo. Indicating that high lying areas provide suitable refuge for leopards and are key areas for movement corridor planning. These density estimates are similar to previous single maximum likelihood SCR density estimate studies in the Little Karoo and the Western Cape province. Results from this study indicate the leopards have persisted in the Little Karoo over the study period and suggest that the population may be increasing. Further research on what is driving this population shift is needed, but the results serve as an encouraging sign for leopard conservation in the Little Karoo.

Research conducted in partial fulfilment of requirements for the degree of Master of Science in Conservation Biology

U.S. Census Bureau QuickFacts statistics for Cape Coral city, Florida. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Abstract

The survey, which covers the two neighbourhoods of Imizamo Yethu and Hout Bay Harbour (Hangberg) in the suburb of Hout Bay, Cape Town, was conducted in November and December 2005.

Geographic coverage

The survey covers two neighbourhoods in the suburb of Hout Bay, Cape Town.

Analysis unit

Households

Universe

The survey covers the population living in the two neighbourhoods of Imizamo Yethu and Hout Bay Harbour (Hangberg) in the suburb of Hout Bay, Cape Town

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Research instrument

Between March and September 2005 the Centre for Actuarial Research (CARe) the Southern Africa Labour and Development Research Unit (SALDRU) at the University of Cape Town devised the questionnaire which developed from a number of earlier drafts. It drew on those questionnaires used in the 1993 Project for Statistics on Living Standards and Development (PSLSD), the 1996 South African Census, the 1999 Integrated Family Survey (Langeberg Survey), the 2000 Khayelitsha/Mitchell’s Plain Survey (KMPS 2000), and the 2001 South African Census. The pre-final draft was extensively discussed with staff from Citizen Surveys, Cape Town, and considerably amended and reformatted. The questionnaire was presented and discussed at a workshop held at the University of Cape Town on the 8th of November 2005 and slight amendments were made.

U.S. Census Bureau QuickFacts statistics for Cape Canaveral city, Florida. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.