Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

The estimated population of all ages in Manitoba stood at ************ people in 2024. Between 1971 and 2024, the estimated population rose by ******* people, though the increase followed an uneven trajectory rather than a consistent upward trend.

This statistic shows the population of Manitoba, Canada in 2022, by age and sex. In 2022, there were ******* females 65 years of age and over in Manitoba.

In 2048, the population in Manitoba is projected to reach about 1.84 million people. This is compared to a population of 1.46 million people in 2024.

This table contains 13 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia ...).

View monthly updates and historical trends for Manitoba Male Population. Source: Statistics Canada. Track economic data with YCharts analytics.

Contained within the 1st Edition (1906) of the Atlas of Canada is a plate that shows two maps. The maps show the density of population per square mile for every township in Manitoba, Saskatchewan, British Columbia, Alberta, circa 1901. The statistics from the 1901 census are used, yet the population of Saskatchewan and Alberta is shown as confined within the vicinity of the railways, this is because the railways have been brought up to date of publication, 1906. Cities and towns of 5000 inhabitants or more are shown as black dots. The size of the circle is proportionate to the population. The map uses eight classes, seven of which are shades of brown, more densely populated portions are shown in the darker tints. Numbers make it clear which class is being shown in any one township. Major railway systems are shown. The map also displays the rectangular survey system which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

View monthly updates and historical trends for Manitoba Female Population. Source: Statistics Canada. Track economic data with YCharts analytics.

View monthly updates and historical trends for Manitoba Youth Population. Source: Statistics Canada. Track economic data with YCharts analytics.

View monthly updates and historical trends for Manitoba Population. Source: Statistics Canada. Track economic data with YCharts analytics.

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate that shows two maps. The first map shows the density of population per square mile for every township in British Columbia and Alberta, circa 1911. The second map shows the density of population per square mile for every township in Manitoba and Saskatchewan, circa 1911. Communities with a population greater than 5000 people are shown as proportional dots on the map. In addition, major railway systems displayed. The map displays the rectangular survey system which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

Projected population according to various scenarios, age groups and gender, Canada, provinces and territories.

The labour productivity in all industries in Manitoba decreased to 56.6 chained (2012) dollars per hour since the previous year. Nevertheless, the last two years recorded a significant higher labour productivity than the preceding years.Find more key insights for the labour productivity in all industries in countries and regions like labour productivity in all industries (Nova Scotia), labour productivity in business sector industries (Canada), and labour productivity in all industries (New Brunswick).

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate map that shows 2 maps. The first map shows the origin of the population in Manitoba and Saskatchewan, circa 1911. The second map shows the origin of the population in British Columbia and Alberta, circa 1911A varying number of ethnic groups are shown, but always included are: English, Scotch [Scottish], Irish, French and German. People of British origin predominate in all provinces, except Quebec, where the French predominate. There is a cosmopolitan population due to immigration from Great Britain and Europe, but British are the predominating people in British Columbia and Alberta. Major railway systems are displayed, which extend into the U.S. The map presents the rectangular survey system, which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

This statistic shows the distribution of the gross domestic product (GDP) of Manitoba, Canada, in 2021, by industry. In that year, the construction industry accounted for almost seven percent of the GDP of Manitoba.

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.

In order to anticipate the impact of local public policies, a synthetic population reflecting the characteristics of the local population provides a valuable test bed. While synthetic population datasets are now available for several countries, there is no open-source synthetic population for Canada. We propose an open-source synthetic population of individuals and households at a fine geographical level for Canada for the years 2021, 2023 and 2030. Based on 2016 census data and population projections, the synthetic individuals have detailed socio-demographic attributes, including age, sex, income, education level, employment status and geographic locations, and are related into households. A comparison of the 2021 synthetic population with 2021 census data over various geographical areas validates the reliability of the synthetic dataset. Users can extract populations from the dataset for specific zones, to explore ‘what if’ scenarios on present and future populations. They can extend the dataset using local survey data to add new characteristics to individuals. Users can also run the code to generate populations for years up to 2042.

To capture the full social and economic benefits of AI, new technologies must be sensitive to the diverse needs of the whole population. This means understanding and reflecting the complexity of individual needs, the variety of perceptions, and the constraints that might guide interaction with AI. This challenge is no more relevant than in building AI systems for older populations, where the role, potential, and outstanding challenges are all highly significant.

The RAIM (Responsible Automation for Inclusive Mobility) project will address how on-demand, electric autonomous vehicles (EAVs) might be integrated within public transport systems in the UK and Canada to meet the complex needs of older populations, resulting in improved social, economic, and health outcomes. The research integrates a multidisciplinary methodology - integrating qualitative perspectives and quantitative data analysis into AI-generated population simulations and supply optimisation. Throughout the project, there is a firm commitment to interdisciplinary interaction and learning, with researchers being drawn from urban geography, ageing population health, transport planning and engineering, and artificial intelligence.

The RAIM project will produce a diverse set of outputs that are intended to promote change and discussion in transport policymaking and planning. As a primary goal, the project will simulate and evaluate the feasibility of an on-demand EAV system for older populations. This requires advances around the understanding and prediction of the complex interaction of physical and cognitive constraints, preferences, locations, lifestyles and mobility needs within older populations, which differs significantly from other portions of society. With these patterns of demand captured and modelled, new methods for meeting this demand through optimisation of on-demand EAVs will be required. The project will adopt a forward-looking, interdisciplinary approach to the application of AI within these research domains, including using Deep Learning to model human behaviour, Deep Reinforcement Learning to optimise the supply of EAVs, and generative modelling to estimate population distributions.

A second component of the research involves exploring the potential adoption of on-demand EAVs for ageing populations within two regions of interest. The two areas of interest - Manitoba, Canada, and the West Midlands, UK - are facing the combined challenge of increasing older populations with service issues and reducing patronage on existing services for older travellers. The RAIM project has established partnerships with key local partners, including local transport authorities - Winnipeg Transit in Canada, and Transport for West Midlands in the UK - in addition to local support groups and industry bodies. These partnerships will provide insights and guidance into the feasibility of new AV-based mobility interventions, and a direct route to influencing future transport policy. As part of this work, the project will propose new approaches for assessing the economic case for transport infrastructure investment, by addressing the wider benefits of improved mobility in older populations.

At the heart of the project is a commitment to enhancing collaboration between academic communities in the UK and Canada. RAIM puts in place opportunities for cross-national learning and collaboration between partner organisations, ensuring that the challenges faced in relation to ageing mobility and AI are shared. RAIM furthermore will support the development of a next generation of researchers, through interdisciplinary mentoring, training, and networking opportunities.

The provide detailed statistical tables for 18 scenarios by single year of the projection period (2001 to 2017). For each of the scenarios, data are available for persons who identify with each of the following three groups: the North American Indian population, the Métis or the Inuit. All three groups were projected separately for each of the ten provinces and three territories. However, the subprovincial and subterritorial level shown for the three groups varies as it depends on the groups' size. For the North American Indians, future numbers were calculated for the urban parts of all census metropolitan areas (CMAs), urban areas outside CMAs, rural areas and reserves. For the Métis, places of residence were grouped into urban parts of CMAs, urban areas outside CMAs and rural areas, which also include reserves. Because of their relatively small size, the Inuit population was projected separately for urban and rural locations only. This information is further broken down by age and sex. The 18 scenarios, as well as scenario-specific assumptions on the future trend in fertility and internal migration, are presented in the table below. In addition to these two components of population growth, all scenarios assumed declining mortality and negligible importance of international migration to the change of the size of three Aboriginal groups. The statistical tables of this CD-ROM are organized into three sections: Aboriginal groups - The projected population by Aboriginal group, type of residence, province/territory and sex for the 18 scenarios by single year from 2001 to 2017; Age and sex - The projected population by Aboriginal group, type of residence, age group and sex for the 18 scenarios by single year from 2001 to 2017; and Province/territory - The projected total Aboriginal population by province/territory, age group, sex and type of residence for the 18 scenarios for 2001 and 2017. The statistical tables are supplementary to the publication Projections of the Aboriginal populations, Canada, provinces and territories: 2001 to 2017 (catalogue no. 91-547).

The Manitoba Longitudinal Study of Young Adults (MLSYA) was a five-year longitudinal study conducted by Liquor and Gaming Authority of Manitoba (LGA), formerly the Manitoba Gaming Control Commission (MGCC); the Addictions Foundation of Manitoba; and the former Manitoba Lotteries Corporation. The study followed a sample of Manitobans between the ages of 18 and 20 from 2007 and 2011. The aim of the study was to develop a better understanding of protective facts that promote responsible gambling and risk factors for gambling-related harms. In addition to gambling-specific data, the MLSYA study includes: Psychosocial indicators Demographic characteristics Measures of alcohol and drug use among participants The final sample for all waves of data included 516 participants. Participants were on average 18.9 years of age at recruitment and 22.2 years of age at study completion. LGA commissioned Prairie Research Associates Inc. to recruit participants and collect data for the MLSYA. While the sample is not truly random, it is reasonably representative of the Manitoba population, other than an overrepresentation of participants living in Winnipeg. Participants were recruited through various methods. This included random-digit dialing, onsite casino recruitment, and advertisements at post-secondary institutions and VLT lounges. At each subsequent wave, past participants were contacted and asked to take part in the next wave of the study. Wave 1 data was collected between November 2007 and October 2002. Wave 2 data was collected between December 2008 and December 2009. Wave 3 data was collected between May and December 2010. Wave 4 data was collected between May and December 2011. Additional information on sampling, retention, study variables, and survey questionnaires can be found in the accompanying summary report and codebook.

This statistic shows the average weekly earnings of employees in Manitoba, Canada from 2001 to 2022. In 2022, salaried employees in Manitoba earned 1,395.18 Canadian dollars on average per week, and hourly employees earned an average of 768.12 Canadian dollars per week.