This statistic shows the biggest cities in Kazakhstan in 2023. In 2023, approximately **** million people lived in Almaty, making it the biggest city in Kazakhstan.

Kazakhstan KZ: Population in Largest City data was reported at 1,547,257.000 Person in 2017. This records an increase from the previous number of 1,534,894.000 Person for 2016. Kazakhstan KZ: Population in Largest City data is updated yearly, averaging 1,069,962.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,547,257.000 Person in 2017 and a record low of 528,653.000 Person in 1960. Kazakhstan KZ: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

As of September 2020, Almaty, the largest city in Kazakhstan with a population of over *********** inhabitants accounting for ** percent of the total population of the country, offered by far the largest number of public bus routes - a total of ***. The capital of Kazakhstan, Nur-Sultan, followed next with *** public bus routes available for its locals and visitors.

Actual value and historical data chart for Kazakhstan Population In Largest City

Kazakhstan KZ: Population in Largest City: as % of Urban Population data was reported at 16.112 % in 2017. This records a decrease from the previous number of 16.205 % for 2016. Kazakhstan KZ: Population in Largest City: as % of Urban Population data is updated yearly, averaging 12.242 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 16.395 % in 2014 and a record low of 11.431 % in 1967. Kazakhstan KZ: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Abstract

The Kazakhstan Multiple Indicator Cluster Survey (MICS) was conducted in 2015 by the Statistics Committee of the Ministry of National Economy of the Republic of Kazakhstan (herein MNE RK).

This is the third MICS Survey in Kazakhstan. The findings from these surveys were used in development and implementation of state programmes in the areas of mother and child health, as well as country programmes of the United Nation Children’s Fund (UNICEF) in Kazakhstan, highlighting the need to improve the statistical data management system with regard to children. Such surveys are crucially important in terms of assessing the state of children and women in Kazakhstan as they provide unique information for development of the national child-centred policy and for international positioning of Kazakhstan. The survey provides statistically sound and internationally comparable data essential for development of evidence base and programmes, and for monitoring country progress towards national goals and global (international) commitments. Among these global commitments are those emanating from international agreements - the World Fit for Children Declaration and its Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs). In addition, the 2015 Kazakhstan MICS results will contribute to establishing a baseline for monitoring the state of women and children in the context of the Sustainable Development Goals (SDGs).

OBJECTIVES

• To provide up-to-date information for assessing the situation of children and women in the Republic of Kazakhstan;

• To collect information that will help to improve national policies in the area of childhood and motherhood protection;

• To generate data for the critical assessment of the progress made in various areas, and to put additional efforts in areas that require more attention;

• To collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To contribute to the generation of baseline data for the post-2015 agenda;

• To contribute to the improvement of data and monitoring systems in the Republic of Kazakhstan and to strengthen technical expertise in the design and implementation of such systems as well as in a better analysis of available data.

Geographic coverage

National level, for urban and rural areas, and for 16 administrative districts (14 regions and 2 cities) of the country: Akmola, Aktobe, Almaty oblast, Atyrau, West Kazakhstan, Zhambyl, Karaganda, Kostanai, Kyzylorda, Mangistau, South Kazakhstan, Pavlodar, North Kazakhstan and East Kazakhstan regions, and two large cities Astana and Almaty. Urban and rural areas in each of the 14 regions and 2 large cities of republican significance - Astana and Almaty - were defined as the sampling strata.

Analysis unit

• Individuals

• Households

Universe

All de jure household members (usual residents), all women aged 15-49 years and all children under 5.

Kind of data

Sample survey data [ssd]

Sampling procedure

The database and cartographic materials of the 2009 National Population Census (2009 Census) in the Republic of Kazakhstan were used in the process forming the sampling frame. The census enumeration areas (EAs) formed for the Census were used as the primary sampling units (PSUs).

The urban and rural areas within each region were identified as the main sampling strata and the sample was selected in two stages. In total, 30 strata were formed - 16 urban including two large cities and 14 rural. At the first sampling stage within each stratum, 840 census enumeration areas were selected systematically with probability proportional to size. At the second sampling stage, upon conducting a household listing within the selected enumeration areas, a random systematic sample of 20 households was drawn in each sample enumeration area, for a total sample size of 16,800 households.

Out of 840 clusters, which were liable for verification, cluster #338, located in the Karaganda region, was inaccessible due to the fact that this territory is under a long-term lease to the Russian Federation and thus under its jurisdiction.

The sample was stratified by region, urban and rural areas, and is not self-weighted. The sample weights are used for reporting nationally representative results. A more detailed description of the sample design can be found in the Final Report (Appendix A, Sample Design) attached as Related Material.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a questionnaire for individual women administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire, administered to mothers (or primary caretakers) of all children under 5 living in the household that included a form for collecting vaccination records at Health Facilities for children under 3.

The Fertility module was included in order to be able to calculate indicators concerning total fertility rate and adolescent birth rate. From the onset, it was decided that childhood mortality indicators will not be calculated on the basis of this survey. Following the 2013 UN Inter-agency Group for Child Mortality Estimation (IGME) mission to Kazakhstan, which assessed that the official registration of births and deaths of children aged 0 to 5 years in the country was in line with international standards, the government made a decision to use infant and child mortality data generated by the official statistics, taking into account the adjustments of the IGME.

The Questionnaire for Children Under Five was administered to mothers (or primary caretakers) of children under 5 years of age living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed.

An additional form was used for all children aged 0-2 years with a completed Questionnaire for Children Under Five, the Appendix for Data Collection at Health Facility About Immunization, to record vaccinations from the registries at health facilities.

The questionnaires are based on the MICS5 model questionnaires. From the MICS5 model English and Russian versions, the questionnaires were customised for 2015 Kazakhstan MICS and translated into the Kazakh language. The questionnaires in the Kazakh and Russian languages were pre-tested in Astana city and in the urban and rural settlements of Karaganda region in May 2015. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the 2015 Kazakhstan MICS questionnaires is provided as Related Material.

In addition to the administration of questionnaires, fieldwork teams tested salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weight and height of children under 5 years of age.

Cleaning operations

Data entry was done using the CSPro software, Version 5.0. The data entry was done on 10 desktop computers by 10 data entry operators and overseen by 2 office editors (questionnaire administrator and data entry editor), as well as by one data entry supervisor. For quality assurance purposes, all questionnaires were entered twice and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS programme and adapted to the 2015 Kazakhstan MICS questionnaires were used throughout. Data processing began in parallel with data collection on 15 September and was completed in December 2015. Data was analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntaxes and tabulation plans developed by UNICEF were customized and used for this purpose.

Response rate

Of the 16,791 households in the sample, 16,605 households were inhabited. Of these, 16,500 households were successfully interviewed: the proportion of interviewed households amounted to 99.4 percent. 12,910 women aged 15-49 years were identified in the interviewed households, of which 12,670 women were successfully interviewed: the proportion of female respondents in interviewed households was 98.1 percent. The list of household members in the household Questionnaire identified 5,561 children under 5. Questionnaires were completed for 5,510 children, which corresponds to 99.1 percent response rate for the interviewed households.

The household response rates in urban and rural areas were more than 99 percent, and by regions - more than 98 percent.

Sampling error estimates

The sample of respondents selected in the Multiple Indicator Cluster Survey - 2015 Kazakhstan MICS - is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variation or variability is not known exactly, but can be estimated statistically from the survey data.

The following sampling

About this dataset

Context

This list ranks the 1 cities in the Big Horn County, MT by Kazakh population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Kazakh Population: This column displays the rank of city in the Big Horn County, MT by their Kazakh population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Kazakh Population: The Kazakh population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Kazakh. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Big Horn County Kazakh Population: This tells us how much of the entire Big Horn County, MT Kazakh population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

Techsalerator’s Location Sentiment Data for Kazakhstan

Techsalerator’s Location Sentiment Data for Kazakhstan offers a comprehensive dataset essential for businesses, researchers, and policymakers. This dataset provides valuable insights into regional sentiment trends, public opinions, and social dynamics across various locations in Kazakhstan.

For access to the full dataset, contact us at info@techsalerator.com or visit Techsalerator Contact Us.

Techsalerator’s Location Sentiment Data for Kazakhstan

Techsalerator’s Location Sentiment Data for Kazakhstan delivers an in-depth analysis of public sentiment across urban, suburban, and rural areas. This dataset is crucial for market research, social studies, brand reputation analysis, and policy-making.

Top 5 Key Data Fields

• Geographical Sentiment Mapping – Identifies sentiment trends across different cities, districts, and rural areas in Kazakhstan.
• Public Opinion Scores – Measures positive, neutral, and negative sentiment based on real-time social and online interactions.
• Industry-Specific Sentiment – Analyzes how different sectors, such as finance, retail, and hospitality, are perceived across locations.
• Event-Triggered Sentiment Changes – Tracks fluctuations in sentiment caused by political events, economic changes, or major happenings.
• Social Media and News Sentiment – Aggregates sentiment from social platforms, news articles, and online forums for a comprehensive outlook.

Top 5 Location Sentiment Trends in Kazakhstan

• Urban vs. Rural Sentiment Divide – Differences in sentiment between major cities like Almaty and Astana versus rural regions.
• Economic and Business Perception – Public perception of business growth, employment trends, and investment climate in different regions.
• Political Sentiment Shifts – Changes in public opinion surrounding government policies, elections, and social reforms.
• Tourism and Hospitality Sentiment – Analysis of traveler reviews, hospitality service ratings, and regional attractiveness for tourists.
• Environmental and Climate Sentiment – Public concerns regarding environmental changes, pollution levels, and sustainability efforts.

Top 5 Applications of Location Sentiment Data in Kazakhstan

• Market Research and Business Strategy – Helps businesses tailor products and services based on regional sentiment insights.
• Government and Policy Making – Assists policymakers in understanding public sentiment towards reforms and initiatives.
• Brand and Reputation Management – Enables companies to monitor and improve brand perception across different locations.
• Media and Journalism – Supports news agencies in tracking public reactions to major events and policy changes.
• Tourism and Real Estate Development – Provides insights into regional attractiveness and customer satisfaction in key areas.

Accessing Techsalerator’s Location Sentiment Data

To obtain Techsalerator’s Location Sentiment Data for Kazakhstan, contact info@techsalerator.com with your specific requirements. Techsalerator provides customized datasets based on requested fields, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Geographical Sentiment Mapping
• Public Opinion Scores
• Industry-Specific Sentiment
• Event-Triggered Sentiment Changes
• Social Media and News Sentiment
• Political and Economic Sentiment Trends
• Consumer Feedback and Reviews
• Regional Comparison Insights
• Real-Time Sentiment Tracking
• Contact Information

For in-depth insights into location-based sentiment trends in Kazakhstan, Techsalerator’s dataset is an essential tool for businesses, researchers, and government agencies.

About this dataset

Context

This list ranks the 1 cities in the Major County, OK by Kazakh population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Kazakh Population: This column displays the rank of city in the Major County, OK by their Kazakh population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Kazakh Population: The Kazakh population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Kazakh. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Major County Kazakh Population: This tells us how much of the entire Major County, OK Kazakh population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

Abstract

The main objectives of sampling household budget survey are:

1) obtaining representative and reliable economic and statistical information about the level of the population in general and of vulnerable sections in particular it;

2) use of data for poverty monitoring;

3) establishing an operational data collection and processing with the use of computer equipment and modern technology.

Geographic coverage

National coverage

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling of households was created by multi-probabilistic (random) sample. This principle guarantees the independence of the selection of the sample results and avoid deliberate its mistakes. Formation of a sample of households was carried out by the territorial principle-based register (list) of housing facilities, set up following the National Census of the Republic of Kazakhstan. Network representative as to the national and at regional level.

General population was divided into six strata: large, medium and small cities of Almaty, Astana, and the countryside.

• The first stratum includes households of major cities with the number of households over 30 thousand units.
• The second stratum comprises households with medium-sized cities of households over 10 thousand units, but less than 30 thousand.
• The third stratum includes households in small towns and townships with the number of households no more than 10 thousand units.
• The fourth stratum comprises households in Almaty.
• The fifth stratum includes households of the city of Astana.
• The sixth stratum includes households of rural settlements.

The sample size was formed on the basis of the objectives of the survey, the degree of heterogeneity of the population studied in terms of properties and financing. The sample size for each stratum was determined using the following formula:

                       Ni
                  ni =-------*n ,
                       N

where:

n = 12000 ni - rounded to a multiple of 30, i = 1, 2, 3, 4, 5, 6.

All cities included in the first stratum, Almaty and Astana were selected with a probability equal to unity. Therefore, in the first stratum sample size of households was determined for each of the following formula:

                       N1j
                 n1j =-------* n1,
                       N1

where:

N1 - all households first stratum, N1j - the number of households of the j-th first stratum, n1 - a sample size first stratum, n1j - a sample size of the j-th first stratum (values rounded to a multiple of 30)

The sample medium, small cities and towns by the method of simple random sampling (PSV) using the software package SPSS. All medium-sized cities that are included in the second stratum, located from west to east in the following order: 1. West Kazakhstan region; 2. Atyrau region; 3. Mangystau; 4. Aktobe region; 5. Kyzylorda region; 6. Kostanay; 7. South Kazakhstan region; 8. Aqmola; 9. Karaganda region; 10. North Kazakhstan region; 11. Zhambyl; 12. Pavlodar region; 13. Almaty region; 14. East Kazakhstan region.

Mode of data collection

Face-to-face [f2f]

About this dataset

Context

This list ranks the 2 cities in the Big Stone County, MN by Kazakh population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Kazakh Population: This column displays the rank of city in the Big Stone County, MN by their Kazakh population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Kazakh Population: The Kazakh population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Kazakh. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Big Stone County Kazakh Population: This tells us how much of the entire Big Stone County, MN Kazakh population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.