About this dataset

Context

The dataset tabulates the Alberta population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Alberta. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 142 (57.03% of the total population). 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 cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Alberta population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Alberta is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Alberta is shown in the following column.

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 Alberta Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Alberta population by age. The dataset can be utilized to understand the age distribution and demographics of Alberta.

Content

The dataset constitues the following three datasets

• Alberta, VA Age Group Population Dataset: A complete breakdown of Alberta age demographics from 0 to 85 years, distributed across 18 age groups
• Alberta, VA Age Cohorts Dataset: Children, Working Adults, and Seniors in Alberta - Population and Percentage Analysis
• Alberta, VA Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

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/.

The Seniors, Community and Social Services Delivery Zones dataset is comprised of all the polygons that represent the service delivery regions established for the Ministry of Seniors, Community and Social Services. Seniors, Community and Social Services delivers services and supports to Albertans in a complex and interconnected environment of substantial change, both externally and internally. Externally, a diverse population, an economic downturn, and relationships with families and stakeholders affect how the department conducts its business. Internally, the department continues to transform the way it supports Albertans through a person-centred, integrated service delivery model that recognizes the unique circumstances, experiences and strengths of individuals and families.

About this dataset

Context

The dataset tabulates the Alberta population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Alberta. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 41 (47.67% of the total population). 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 cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Alberta population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Alberta is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Alberta is shown in the following column.

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 Alberta Population by Age. You can refer the same here

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

This Seniors, Community and Social Services (SCSS) dataset describes the monthly Assured Income for the Severely Handicapped (AISH) caseload in Alberta. The AISH program provides financial and health benefits to eligible adult Albertans with a permanent medical condition that prevents them from earning a living. Caseloads are reported as the actual volume each month and by the Alberta government’s fiscal year. Depending on an individual’s situation, some AISH benefits may also be provided for a spouse or partner and dependent children. Monthly caseloads are also shown as a portion of the entire Alberta population; and by gender, age, primary medical condition, family composition, employment participation and six service delivery regions across the province. For locations of AISH delivery regions, choose the Alberta Seniors, Community and Social Services Regions Map within the Resources section.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

This Seniors, Community and Social Services (SCSS) dataset describes the monthly Assured Income for the Severely Handicapped (AISH) caseload in Alberta. The AISH program provides financial and health benefits to eligible adult Albertans with a permanent medical condition that prevents them from earning a living. Caseloads are reported as the actual volume each month and by the Alberta government’s fiscal year. Depending on an individual’s situation, some AISH benefits may also be provided for a spouse or partner and dependent children. Monthly caseloads are also shown as a portion of the entire Alberta population; and by gender, age, primary medical condition, family composition, employment participation and six service delivery regions across the province. For locations of AISH delivery regions, choose the Alberta Seniors, Community and Social Services Regions Map within the Resources section.

This Seniors, Community and Social Services (SCSS) dataset describes the monthly Income Support caseload in Alberta, including two client groups: those Expected to Work (ETW) and those who have Barriers to Full Employment (BFE). Income Support provides financial benefits to individuals and families who do not have the resources to meet their basic needs, like food, clothing, and shelter. The caseload is defined as the number of households categorized as ETW or BFE during a specific reporting period. Most commonly, this is reported as the average volume for a specific period (e.g., annually). The composition of the caseload is made up of single individuals, lone-parent families, couples with children and couples without children. In April 2018, a breakdown of the number of caseloads by SCSS Regions was added to provide greater context. NOTE: (1) - Due to a change in how region information is tracked within source systems, region caseloads have been updated as of January 2025 to include an additional category 'Unknown', reflecting new postal codes being introduced to the data record within source systems. This change has been retroactively applied to all past data. (2) - All regions report that the primary factor for reduced Income Support caseloads from April-2020 is due to Albertans accessing the federal government’s Canada Emergency Response Benefit (CERB).

About this dataset

Context

The dataset tabulates the Alberta township population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Alberta township. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 472 (59.97% of the total population). 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 cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Alberta township population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Alberta township is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Alberta township is shown in the following column.

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 Alberta township Population by Age. You can refer the same here

Individuals; Tax filers and dependants by total income, sex and age groups (final T1 Family File; T1FF).

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

The number of high school graduates from regular programs for youth, public schools, by age group and sex.

Here we provide one of the first detailed studies of lichen and allied fungi diversity in a continental North American city (Edmonton, Alberta, Canada), including an annotated checklist, images of all species, dichotomous keys, and local distribution maps. Edmonton is the northernmost city in North America with a population of over one million, and an industrial and transportation gateway for much of northern Canada. Lichen-based biomonitoring could be a tool to track airborne pollutants resulting from Edmonton’s growing populace and industrial activity. The first step towards such a program is documenting the diversity and distribution of lichens in the city. To accomplish this, we conducted a city-wide, systematic survey of 191 sites focused on epiphytes growing on deciduous boulevard trees. We augmented that survey with surveys of rare trees, opportunistic collections from river valley and ravine habitats, herbarium collections, phylogenetic analyses of a subset of collections, and observations submitted to online nature-reporting applications. We present ITS sequence barcode data for 33 species, phylogenetic analyses for Candelariaceae, Endocarpon, Flavopunctelia, the Lecanora dispersa group, Lecidella, Peltigera, Physconia, and Punctelia, and detailed descriptions of 114 species in 47 genera and 23 families. Two species are hypothesized to be new to North America (Endocarpon aff. unifoliatum, Lecidella albida), twelve more are new to Alberta (Amandinea dakotensis, Bacidia circumspecta, Candelaria pacifica, Candelariella antennaria, Heterodermia japonica, Lecania naegelii, Lecanora sambuci, Lecanora stanislai, Lecidea erythrophaea, Peltigera islandica, Phaeocalicium aff. tremulicola, and the introduced Xanthoria parietina), and five are putative new species to science (Physcia aff. dimidiata, Physcia aff. stellaris, Phaeocalicium sp., Phaeocalicium aff. tremulicola, Lichenaceae sp.). Illustrations are provided for all species to aid in verification and public outreach. Species richness was highest in foliose lichens (48), followed by crustose and calicioid lichens and allied fungi (41), with the lowest richness in fruticose lichens (25). We did a preliminary assessment of the suitability of species for citizen-science biomonitoring by assessing their distribution across the city, perceptibility to the public, identification accuracy, and, for a subset, how consistently species were surveyed by trained novices. Compared to other urban areas where lichen diversity has been studied, Edmonton is relatively species-rich in calicioids and Peltigera. Promising bioindicators may be limited to chlorolichens, including Caloplaca spp., Evernia mesomorpha, Flavopunctelia spp., Phaeophyscia orbicularis, Physcia adscendens, Physcia aipolia group, Physcia aff. stellaris, Usnea spp., and Xanthomendoza fallax. Other genera that may be responsive to pollutants such as Cladonia and Peltigera were almost exclusively restricted to river valley and ravine ecosystems, limiting their application as bioindicators. Some species commonly used as biomonitors elsewhere were too rare, small, poorly developed, or obscured by more common species locally (e.g., Candelaria concolor s.l., Xanthomendoza hasseana). The low overlap with lists of biomonitoring species from other regions of North America illustrates the necessity of grounding monitoring in knowledge of local diversity. Future augmentation of this list should focus on enhanced sampling of downed wood-, conifer-, and rock-dwelling lichens, particularly crustose species. The next step in developing a biomonitoring program will require modelling species’ responses to known air quality and climatic gradients. Methods Molecular methods. – To verify or aid in the identification of a subset of collections, the internal transcribed spacer (ITS ribosomal DNA; internal transcribed spacer regions 1 and 2 as well as the embedded 5.8S region of the ribosomal rDNA and adjacent sections of the large and small ribosomal subunits, LSU and SSU) was Sanger sequenced by T. Spribille’s lab at the U of A. ITS is the single most sequenced locus in fungi and widely used as a barcode (Hoffman & Lendemer 2018, Schoch et al. 2012,). DNA was extracted using the Qiagen DNeasy Plant Mini Kit following the manufacturer’s instructions, or, in the case of sparse material, the QIAmp DNA Investigator Kit. PCR was performed using ITS1-F (Gardes & Bruns 1993) and ITS4 primers (White et al. 1990), and the KAPA 3G Plant PCR Kit (KAPA Biosystems). The PCR cycle used was: pre-denaturation for 5 min at 95°C, 35 cycles of amplification, each cycle 30 sec at 95°C, 30 sec at 57°C, and 30 sec at 72°C. After the 35 cycles, extension occurred over 7 min of 72°C and then samples were stored at 4°C. PCR products were visualized on agarose gel after electrophoresis and sent for sequencing if a product was seen. Samples with multiple bands were not sent for sequencing due to poor chance of a clear sequence. Prior to sequencing, samples were purified using standard ExoSap protocol. PCR products were sequenced by Psomagen, Inc., USA, and forward sequences were visually examined for errors or ambiguities prior to screening. Phylogenetic analyses. – We screened sequences with BLAST searches against the NCBI nucleotide database to identify sequences that may represent non-target organisms (NCBI Resource Coordinators 2018). The sequences generated for this study were complemented with sequences from GenBank representing additional species and specimens, as well as a small number of sequences from the senior author. For queried sequences of species adequately represented in GenBank, we report similarity metrics with accessioned sequences in the annotated species list. Further analyses including de novo tree construction were conducted for Candelariaceae, Endocarpon, Lecidella, Flavopunctelia, Lecanora dispersa group, Peltigera, Physconia, and Punctelia, as BLAST results were insufficient. For genera requiring phylogenetic analyses, the following steps were common across analyses; specifics for each phylogeny are provided below. Sequences for each analysis were aligned with our query sequence(s) using MAFFT via a web platform (MAFFT ver. 7.49, Katoh et al. 2002, Katoh & Standley 2013, Katoh et al. 2019) or in MegAlign Pro v. 17 (DNASTAR 2021), and visually inspected in BioEdit 7.7.1 (Hall 1999). We used ITSx 1.1 (Bengtsson-Palme et al. 2013) to split sequences into ITS, small subunit, and large subunit files to aid in sequence vetting and where appropriate create partitions for nucleotide substitution model fitting. We visually examined final alignments in BioEdit and trimmed all sites from the alignment present in ≤10% of sequences. Alignments were screened using GUIDANCE2 for ambiguous sites, and analyses were completed with and without ambiguous regions and the resultant trees visually compared. Original fasta files and final alignments are deposited in Dryad, and sequence data are provided in Supplementary Appendix 2. We generated maximum likelihood phylogenetic trees in W-IQ-TREE 1.6.12 (Nguyen et al. 2015, Trifinopoulos et al. 2016) via http://iqtree.cibiv.univie.ac, specifying partitions (partition model: Chernomor et al. 2016), linked branch lengths, automatic model selection (ModelFinder: Kalyaanamoorthy et al. 2017), and free rate heterogeneity. Branch support was analyzed by 1,000 ultrafast bootstraps (UFBoot: Hoang et al. 2018) as well as SH-aLRT single branch tests with 1,000 replicates. Trees were visualized and organized in Dendroscope 3.7.6 (Huson & Scornavacca 2012) and/or MegAlign Pro, and exported to Microsoft Office Professional Plus Powerpoint 2016 for editing. The Candelariaceae phylogeny was generated de novo with seven new sequences from the senior author, GenBank sequences with high BLAST similarity to our new sequences, and sequences from Westberg et al. (2011), Liu & Hur (2018), and Liu et al. (2019). Additional sequences for Candelaria were added from GenBank to increase taxon sampling in that clade. The Endocarpon phylogeny was generated de novo using two new sequences from the senior author, GenBank sequences with high BLAST similarity to our new sequences, and sequences from Zhang et al. (2017). The Flavopunctelia phylogeny was constructed using all accessioned sequences of Flavopunctelia in GenBank, sequences from this study, and GenBank sequences with high BLAST similarity to our new sequences, regardless of determination. The Lecanora dispersa group phylogeny was created by adding new sequences from this study, their top-scoring megablast GenBank sequences, and the ITS of the type of L. lendemeri E. Tripp & C.A. Morse (Tripp et al. 2019) to the multiple sequence alignment from Śliwa et al. 2012 (Treebase study #12681, using ‘mafft—add’ (https://mafft.cbrc.jp/alignment/server/add.html, Katoh & Frith 2012). Similarly, the Physconia phylogeny was compiled using the 60 sequences from Esslinger et al. (2017, deposited in Dryad as https://doi.org/10.5061/dryad.bh7mc), and additional sequences from the senior author, GenBank, and this study. Finally, we aligned five new Punctelia sequences to the ITS portions of the concatenated alignment of Alors et al. (2016), and the ITS alignment of Lendemer & Hodkinson (2010) using ‘mafft—add’. ITS was concatenated with the other loci in Mesquite, and the new multiple sequence alignments were reanalyzed with partitions. For Peltigera sequences, we also used NCBI BLAST with megablast to check the percent of our sequence that was identical to sequences published by F. Lutzoni and J. Miadlikowska Peltigera projects, which we mapped to currently undescribed molecular species delimited by Pardo-De la Hoz et al. (2018) and Magain et al. (2018). For Peltigera section Peltigera we also checked for the presence of species-specific hypervariable region sequences described in Magain et al. (2018). A sterile crust that could not be assigned to genus

Life expectancy at birth and at age 65, by sex, on a three-year average basis.

Seniors safety, including the elimination of neglect, abuse and violence against older persons (hereafter referred to as “senior abuse”), is a national and international priority. In order to develop evidence-based solutions, data on the nature and extend of senior abuse are required. As law enforcement agencies are engaged to respond to some incidents of senior abuse, partnerships with police services can help shed light on what date are collected and how they are used. Justice Canada collaborated with the Edmonton Police Service’s (EPS) Senior Protection Unit to examine data collection practices and responses to senior abuse in Edmonton, Alberta. Alberta has adopted a coordinated community response (CCR) model to help address senior abuse. Under a CCR model, community organizations and service providers collaborate to offer people-centred services for seniors and families of seniors affected by abuse. The goal is to connect clients with the appropriate supports and interventions with respect to housing, finances, legal aid, court support, health services, counselling, and dispute resolution. In Edmonton, the CCR model includes triaging senior abuse cases according to risk level, with the Elder Abuse Resources and Supports Program (EARS) managing low- to medium-risk cases, and the Seniors Protection Partnership (SPP) managing high-risk cases. The EPS’s Senior Protection Unit has dedicated detectives who handle complex and serious senior abuse cases and work in partnership with the SPP, the team managing high-risk cases, while also referring lower-risk cases to EARS, when appropriate. This case study examined 691 senior abuse incidents or suspicions (hereafter referred to as “reports”) from 2015 to 2021, identified using two data sources: the SPP database and the Edmonton Police Reporting and Occurrence System (EPROS), a record management system used by the EPS. This represents all senior abuse reports that came to the attention of the Senior Protection Unit during this period. The study also included two group interviews with 10 key informants, including detectives from the Senior Protection Unit, representatives from the City of Edmonton, and community service providers who are members of Edmonton’s Elder Abuse Consultation Team via the SPP.

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

This SCSS dataset describes quarterly statistics regarding the Citizen's Appeals Panel. The panel provides an appeal process for those who do not agree with decisions made by the Ministry of Seniors, Community and Social Services and the Ministry of Children and Family Services, Ministry of Jobs, Economy and Trade, Ministry of Health and Ministry of Mental Health and Addiction. The service offers impartial, neutral, and unbiased hearings for appeals and renders decisions, within the discretion allowed under relevant legislation that has been vested in adjudication panels, an appeal process that ensures all parties involved have equal opportunity to present their case, hear all evidence presented, assess all written information presented or referenced, and question the validity of any or all of the information presented, and a written decision providing the findings of the hearing. This dataset includes quarterly information on appeals filed, appeals withdrawn, and decisions rendered for each of SCSS's four core legislated programs, Income Support, Assured Income for the Severely Handicapped (AISH), Persons with Developmental Disabilities (PDD) and Family Support for Children with Disabilities (FSCD). Note that all values less than 5 have been suppressed for privacy purposes, and that data for PDD and FSCD appeals are presented annually, to prevent having to suppress data with small sample sizes at the quarterly level.

About this dataset

Context

The dataset tabulates the data for the Alberta, MN population pyramid, which represents the Alberta population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Alberta, MN, is 15.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Alberta, MN, is 71.7.
• Total dependency ratio for Alberta, MN is 87.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Alberta, MN is 1.4.

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 for the Alberta population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Alberta for the selected age group is shown in the following column.
• Population (Female): The female population in the Alberta for the selected age group is shown in the following column.
• Total Population: The total population of the Alberta for the selected age group is shown in the following column.

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 Alberta Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Alberta by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Alberta. The dataset can be utilized to understand the population distribution of Alberta by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Alberta. 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 Alberta.

Key observations

Largest age group (population): Male # 65-69 years (28) | Female # 55-59 years (17). 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

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 Alberta population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Alberta is shown in the following column.
• Population (Female): The female population in the Alberta 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 Alberta 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 Alberta Population by Gender. You can refer the same here