Statistics Canada data from the 2021 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/5bk4-5txu.

Source: Statistics Canada, 2021 Census of Population, 2023-06-23. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2023 Census of Population, . This does not constitute an endorsement by Statistics Canada of this product."

Missing Values: - Default missing value .. Not available for a specific reference period x Suppressed to meet the confidentiality requirements of the Statistics Act ... Not applicable F Too unreliable to be published

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.

This table presents the 2021 and 2016 population counts and the 2021 dwelling counts, land area and population density for a census metropolitan area or a tracted census agglomeration and the census tracts within the census metropolitan area or tracted census agglomeration.

Statistics Canada data from the 2016 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/3did-mjnj.

Source: Statistics Canada, 2016 Census of Population, 2021-01-13. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2016 Census of Population, . This does not constitute an endorsement by Statistics Canada of this product."

This map features the World Population Density Estimate 2016 layer for the Caribbean region. The advantage population density affords over raw counts is the ability to compare levels of persons per square kilometer anywhere in the world. Esri calculated density by converting the the World Population Estimate 2016 layer to polygons, then added an attribute for geodesic area, which allowed density to be derived, and that was converted back to raster. A population density raster is better to use for mapping and visualization than a raster of raw population counts because raster cells are square and do not account for area. For instance, compare a cell with 185 people in northern Quito, Ecuador, on the equator to a cell with 185 people in Edmonton, Canada at 53.5 degrees north latitude. This is difficult because the area of the cell in Edmonton is only 35.5% of the area of a cell in Quito. The cell in Edmonton represents a density of 9,810 persons per square kilometer, while the cell in Quito only represents a density of 3,485 persons per square kilometer. Dataset SummaryEach cell in this layer has an integer value with the estimated number of people per square kilometer likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers: World Population Estimate 2016: this layer contains estimates of the count of people living within the the area represented by the cell. World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: https://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is primarily intended for cartography and visualization, but may also be useful for analysis, particularly for estimating where people living above specified densities. There are two processing templates defined for this layer: the default, "World Population Estimated 2016 Density Classes" uses a classification, described above, to show locations of levels of rural and urban populations, and should be used for cartography and visualization; and "None," which provides access to the unclassified density values, and should be used for analysis. The breaks for the classes are at the following levels of persons per square kilometer:100 - Rural (3.2% [0.7%] of all people live at this density or lower) 400 - Settled (13.3% [4.1%] of all people live at this density or lower)1,908 - Urban (59.4% [81.1%] of all people live at this density or higher)16,978 - Heavy Urban (13.0% [24.2%] of all people live at this density or higher)26,331 - Extreme Urban (7.8% [15.4%] of all people live at this density or higher) Values over 50,000 are likely to be erroneous due to spatial inaccuracies in source boundary dataNote the above class breaks were derived from Esri's 2015 estimate, which have been maintained for the sake of comparison. The 2015 percentages are in gray brackets []. The differences are mostly due to improvements in the model and source data. While improvements in the source data will continue, it is hoped the 2017 estimate will produce percentages that shift less.For analysis, Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the average, highest, or lowest density within those zones.

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-North West for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-Riverview for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-Strathcona for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

(StatCan Product) Employed by industries and sectors (NAICS 2007 – 1, 2, 3 and 4 digits) for Canada, selected provinces (QC, ON, AB and BC), Edmonton (CMA) and Calgary (CMA) (annual averages). Customization details: This information product has been customized to present information on the employed by industries: - TABLE 1: Employed by industries (NAICS 2007 – 1, 2, 3 and 4 digits) for Canada, selected provinces (Quebec, Ontario, Alberta and British Columbia) and the Alberta Census Metropolitan Areas (CMA) of Edmonton and Calgary – Annual Averages from 2001 to 2011 (in thousands). Labour Force Survey The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. Target population The LFS covers the civilian, non-institutionalized population 15 years of age and over. It is conducted nationwide, in both the provinces and the territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Armed Forces and the institutionalized population. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over. National Labour Force Survey estimates are derived using the results of the LFS in the provinces. Territorial LFS results are not included in the national estimates, but are published separately. Instrument design The current LFS questionnaire was introduced in 1997. At that time, significant changes were made to the questionnaire in order to address existing data gaps, improve data quality and make more use of the power of Computer Assisted Interviewing (CAI). The changes incorporated included the addition of many new questions. For example, questions were added to collect information about wage rates, union status, job permanency and workplace size for the main job of currently employed employees. Other additions included new questions to collect information about hirings and separations, and expanded response category lists that split existing codes into more detailed categories. Sampling This is a sample survey with a cross-sectional design. Data sources Responding to this survey is mandatory. Data are collected directly from survey respondents. Data collection for the LFS is carried out each month during the week following the LFS reference week. The reference week is normally the week containing the 15th day of the month. LFS interviews are conducted by telephone by interviewers working out of a regional office CATI (Computer Assisted Telephone Interviews) site or by personal visit from a field interviewer. Since 2004, dwellings new to the sample in urban areas are contacted by telephone if the telephone number is available from administrative files, otherwise the dwelling is contacted by a field interviewer. The interviewer first obtains socio-demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces. The majority of subsequent interviews are conducted by telephone. In subsequent monthly interviews the interviewer confirms the socio-demographic information collected in the first month and collects the labour force information for the current month. Persons aged 70 and over are not asked the labour force questions in subsequent interviews, but rather their labour force information is carried over from their first interview. In each dwelling, information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting, which accounts for approximately 65% of the information collected, is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent. Error detection The LFS CAI questionnaire incorporates many features that serve to maximize the quality of the data collected. There are many edits built into the CAI questionnaire to compare the entered data against unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy. As well, for most questions the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question. Once the data is received back at head office an extensive series of processing steps is undertaken to thoroughly verify each record received. This includes the coding of industry and occupation information and the review of interviewer entered notes. The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items, and the correction of such conditions. Since the true value of each entry on the questionnaire is not known, the identification of errors can be done only through recognition of obvious inconsistencies (for example, a 15 year-old respondent who is recorded as having last worked in 1940). Estimation The final step in the processing of LFS data is the assignment of a weight to each individual record. This process involves several steps. Each record has an initial weight that corresponds to the inverse of the probability of selection. Adjustments are made to this weight to account for non-response that cannot be handled through imputation. In the final weighting step all of the record weights are adjusted so that the aggregate totals will match with independently derived population estimates for various age-sex groups by province and major sub-provincial areas. One feature of the LFS weighting process is that all individuals within a dwelling are assigned the same weight. In January 2000, the LFS introduced a new estimation method called Regression Composite Estimation. This new method was used to re-base all historical LFS data. It is described in the research paper ""Improvements to the Labour Force Survey (LFS)"", Catalogue no. 71F0031X. Additional improvements are introduced over time; they are described in different issues of the same publication. Data accuracy Since the LFS is a sample survey, all LFS estimates are subject to both sampling error and non-sampling errors. Non-sampling errors can arise at any stage of the collection and processing of the survey data. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors and other types of processing errors. Non-response to the LFS tends to average about 10% of eligible households. Interviews are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households. Each month, after all attempts to obtain interviews have been made, a small number of non-responding households remain. For households non-responding to the LFS, a weight adjustment is applied to account for non-responding households. Sampling errors associated with survey estimates are measured using coefficients of variation for LFS estimates as a function of the size of the estimate and the geographic area.

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-Whitemud for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

Statistics Canada data from the 2021 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/5bk4-5txu.

Source: Statistics Canada, 2021 Census of Population, 2023-06-23. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2021 Census of Population, . This does not constitute an endorsement by Statistics Canada of this product."

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-Rutherford for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

Statistics Canada data from the 2021 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/5bk4-5txu.

Source: Statistics Canada, 2021 Census of Population, 2023-06-23. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2023 Census of Population, . This does not constitute an endorsement by Statistics Canada of this product."

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.

Presents detailed demographic and socio-economic information for the Provincial Electoral Division of Edmonton-Castle Downs for the 2023 provincial general election. Data have been specifically tabulated from the 2021 Census of Canada and include age, gender, marital status, household types and family structure, language, Indigenous identity, immigrant population, visible minorities, religion, mobility, dwelling characteristics, education, labour force activity and income. A map of the electoral division is included.

Statistics Canada data from the 2016 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/3did-mjnj.

Source: Statistics Canada, 2016 Census of Population, 2021-01-13. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2016 Census of Population,

Statistics Canada data from the 2016 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/3did-mjnj.

Source: Statistics Canada, 2016 Census of Population, 2021-01-13. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2016 Census of Population,

Statistics Canada data from the 2021 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/5bk4-5txu.

Source: Statistics Canada, 2021 Census of Population, 2023-06-23. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2023 Census of Population, . This does not constitute an endorsement by Statistics Canada of this product."

Statistics Canada data from the 2016 Census of Population, aligned to Edmonton's neighbourhood boundaries. For the neighbourhood boundaries as they were at the time of the census, please see https://data.edmonton.ca/d/3did-mjnj.

Source: Statistics Canada, 2016 Census of Population, 2021-01-13. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Please see https://www.statcan.gc.ca/eng/reference/licence and https://www.statcan.gc.ca/eng/reference/licence-faq for the terms of the Statistics Canada Open Licence.

Note that if you use this data to create another product, an additional acknowledgement is required: "Adapted from Statistics Canada, 2016 Census of Population,