This dataset is a customization of Statistics Canada data to present information on the fiscal year average from April 2015 to March 2016 in Alberta by age, National Occupational Classification (NOC) groups, and wage distribution.

This dataset is a customization of Statistics Canada data to present information on the fiscal year average from April 2015 to March 2016 in Alberta by age, National Occupational Classification (NOC) groups, and wage distribution.

The Population Research Laboratory (PRL) administered the 2015 Alberta Survey A. This survey of households across the province of Alberta continues to enable academic researchers, government departments, and non-profit organizations to explore a wide range of topics in a structured research framework and environment. Sponsors’ research questions are asked together with demographic questions in a telephone interview of Alberta households.

Alberta's occupational outlook provides labour supply forecasts by occupation covering a 10-year forecast period. This dataset presents information on the projected educational attainment levels of Alberta’s population and gives an analysis of graduates in major fields of study at different post-secondary education levels.

This report, Aboriginal People in Alberta, is one of three reports in the Alberta 2006 Census Analysis series that present results and analyses with findings from the 2006 Canadian Census. The 2006 Census Analysis series focuses on labour market activities in Alberta and includes analysis for the current and previous Census year(s). The other two reports in the series are the Alberta Profile and Persons with Disabilities Profile.

This Alberta Official Statistic describes the per capita health service providers in 2011. Per capita health service providers are the number of individuals working in medicine or health occupations per 1,000 people. The population is divided into larger urban centres and rural and small town areas. Within rural and small town Alberta, the population is divided into four categories according to integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% to 49% of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to an urban core) Weak MIZ (where 1% to 4% commute to an urban core) No MIZ (where there are no residents commuting to an urban core)

The 2018-19 Occupational Health and Safety (OHS) survey was the first known occupational health and safety population survey conducted in Alberta. The survey was designed to provide baseline data for future comparisons. The objectives of the survey were to provide data on a variety of factors affecting worker health and safety, understand the relationships between factors affecting worker health and safety, gain insight on worker vulnerability, and understand industry and occupation specific factors over time. A total of 8,464 records were validated and included in the public use data file.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by age group and gender. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Number of employees by North American Industry Classification System (NAICS) and type of employee, last 5 years.

Alberta's occupational outlook provides labour supply forecasts by occupation covering a 10-year forecast period. This report looks at the projected educational attainment levels of Alberta’s population and gives an analysis of graduates in major fields of study at different post-secondary education levels.

(StatCan Product) This information product has been customized to present information on wages of employees by type of work (full- and part-time), immigrant status, industry by sex for Canada and provinces (annual averages).

Number of persons in the labour force (employment and unemployment) and unemployment rate, by North American Industry Classification System (NAICS), gender and age group.

The 2018-19 Occupational Health and Safety (OHS) survey was the first known occupational health and safety population survey conducted in Alberta. The survey was designed to provide baseline data for future comparisons. The objectives of the survey were to provide data on a variety of factors affecting worker health and safety, understand the relationships between factors affecting worker health and safety, gain insight on worker vulnerability, and understand industry and occupation specific factors over time. A total of 8,464 records were validated and included in the public use data file.

This dataset presents information on the projected population size for Alberta as well as the sizes for the following three sub-groups: Indigenous people, visible minorities, and those wjith activity limitations.

This report projects Alberta’s population by age and gender, and by three subgroups: Aboriginal people, visible minorities, and those with activity limitations. These projections and their implications form the main focus of this report.

2011_national_household_survey demography educational_attainment immigrant_population immigrants labour_force_participation occupations population statistics_canada_customized_data

The 2018-19 Occupational Health and Safety (OHS) survey was the first known occupational health and safety population survey conducted in Alberta. The survey was designed to provide baseline data for future comparisons. The objectives of the survey were to provide data on a variety of factors affecting worker health and safety, understand the relationships between factors affecting worker health and safety, gain insight on worker vulnerability, and understand industry and occupation specific factors over time. A total of 8,464 records were validated and included in the public use data file.

(StatCan Product) Labour force, Number of employed and Number of unemployed by selected National Occupational Classification (NOC) (2006 Occupations - Energy Sector) for Canada and Alberta from 1987 to 2012 (annual averages). Customization details: This information product has been customized to present information on the labour force, including the employed and unemployed by occupation specifically within the energy sector for Canada and Alberta. 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.

This table provides the age-standardized mortality rates per 100,000 population, for the three selected causes of death and all causes combined. The three selected causes of death are Circulatory System, Neoplasms and External Causes (Injury). Age standardization is a technique applied to make rates comparable across groups with different age distributions. A simple rate is defined as the number of people with a particular condition divided by the whole population. An age-standardized rate is defined as the number of people with a condition divided by the population within each age group. Standardizing (adjusting) the rate across age groups allows a more accurate comparison between populations that have different age structures. Age standardization is typically done when comparing rates across time periods, different geographic areas, and or population sub-groups (e.g. ethnic group). This indicator dataset contains information at both Local Geographic Area (for example, Lacombe, Red Deer - North, Calgary - West Bow, etc.) and Alberta levels. Local geographic area refers to 132 geographic areas created by Alberta Health (AH) and Alberta Health Services (AHS) based on census boundaries. This table is the part of "Alberta Health Primary Health Care - Community Profiles" report published February 2013

The 2018-19 Occupational Health and Safety (OHS) survey was the first known occupational health and safety population survey conducted in Alberta. The survey was designed to provide baseline data for future comparisons. The objectives of the survey were to provide data on a variety of factors affecting worker health and safety, understand the relationships between factors affecting worker health and safety, gain insight on worker vulnerability, and understand industry and occupation specific factors over time. A total of 8,464 records were validated and included in the public use data file.