Facebook
TwitterBy Throwback Thursday [source]
The dataset contains information on a wide range of religions, including Christianity, Judaism, Islam, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism, Zoroastrianism, Syncretic Religions (religious practices that blend elements from multiple faiths), Animism (belief in spiritual beings in nature), Non-Religious individuals or those without any religious affiliation.
For each religion and region/country combination recorded in the dataset we have the following information:
- Total population: The total population of the region or country.
- Religious affiliation percentages: The percentages of the population that identify with specific religious affiliations.
- Subgroup populations/percentages: The populations or percentages within specific denominations or sects of each religion.
The dataset also provides additional variables like Year and State Name (for regional data) for further analysis.
Understanding the Columns
The dataset contains several columns with different categories of information. Here's a brief explanation of some important columns:
- Year: The year in which the data was recorded.
- Total Population: The total population of a country or region.
- State Name (StateNme): The name of the state or region.
Each religion has specific columns associated with it, such as Christianity, Buddhism, Islam, Hinduism, Judaism, Taoism, Shintoism etc., representing its percentage and population for each category/denomination within that religion.
Selecting Specific Data
If you are interested in exploring data related to a particular religion or geographic location:
To filter data by Religion: Identify relevant columns associated with that religion such as 'Christianity', 'Buddhism', 'Islam', etc., and extract their respective percentage and population values for analysis.
Example: If you want to analyze Christianity specifically, extract columns related to Christianity like 'Christianity (Percent)', 'Christianity (Population)', etc.
Note: There might be multiple columns related to a specific religion indicating different categories or denominations within that religion.
To filter data by Geographic Location: Utilize the 'State Name' column ('StateNme') to segregate data corresponding to different states/regions.
Example: If you want to analyze religious demographics for a particular state/region like California or India:
i) Filter out rows where State Name is equal to California or India.
ii) Extract relevant columns associated with your selected religion as mentioned above.
Finding Trends and Insights
Once you have selected the specific data you are interested in, examine patterns and trends over time or across different regions.
Plotting data using visualizations: Use graphical tools such as line charts, bar charts, or pie charts to visualize how religious demographics have changed over the years or vary across different regions.
Analyzing population proportions: By comparing the percentage values of different religions for a given region or over time, you can gather insights into changes in religious diversity.
Comparing Religions
If you wish to compare multiple religions:
- Comparing religious affiliations across different countries or regions: With data on various religions such as Christianity, Islam, Buddhism, Judaism, Hinduism, etc., researchers can compare the religious affiliations of different countries or regions. This can help in understanding the cultural and religious diversity within different parts of the world.
- Exploring the growth or decline of specific religions: By examining population numbers for specific religions such as Jainism, Taoism, Zoroastrianism, etc., this dataset can be used to investigate the growth or decline of these religious groups over time. Researchers can analyze factors contributing to their popularity or decline in particular regions or countries
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: ThrowbackDataThursday 201912 - Religion.csv | Column name...
Facebook
TwitterBy Throwback Thursday [source]
The dataset includes data on Christianity, Islam, Judaism, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism and various other syncretic and animist religions. For each religion or denomination category, it provides both the total population count and the percentage representation in relation to the overall population.
Additionally, - Columns labeled with Population provide numeric values representing the total number of individuals belonging to a particular religion or denomination. - Columns labeled with Percent represent numerical values indicating the percentage of individuals belonging to a specific religion or denomination within a given population. - Columns that begin with ** indicate primary categories (e.g., Christianity), while columns that do not have this prefix refer to subcategories (e.g., Christianity - Roman Catholics).
In addition to providing precise data about specific religions or denominations globally throughout multiple years,this dataset also records information about geographical locations by including state or country names under StateNme.
This comprehensive dataset is valuable for researchers seeking information on global religious trends and can be used for analysis in fields such as sociology, anthropology studies cultural studies among others
Introduction:
Understanding the Columns:
Year: Represents the year in which the data was recorded.
StateNme: Represents the name of the state or country for which data is recorded.
Population: Represents the total population of individuals.
Total Religious: Represents the total percentage and population of individuals who identify as religious, regardless of specific religion.
Non Religious: Represents the percentage and population of individuals who identify as non-religious or atheists.
Identifying Specific Religions: The dataset includes columns for different religions such as Christianity, Judaism, Islam, Buddhism, Hinduism, etc. Each religion is further categorized into specific denominations or types within that religion (e.g., Roman Catholics within Christianity). You can find relevant information about these religions by focusing on specific columns related to each one.
Analyzing Percentages vs. Population: Some columns provide percentages while others provide actual population numbers for each category. Depending on your analysis requirement, you can choose either column type for your calculations and comparisons.
Accessing Historical Data: The dataset includes records from multiple years allowing you to analyze trends in religious populations over time. You can filter data based on specific years using Excel filters or programming languages like Python.
Filtering Data by State/Country: If you are interested in understanding religious populations in a particular state or country, use filters to focus on that region's data only.
Example - Extracting Information:
Let's say you want to analyze Hinduism's growth globally from 2000 onwards:
- Identify Relevant Columns:
- Year: to filter data from 2000 onwards.
Hindu - Total (Percent): to analyze the percentage of individuals identifying as Hindus globally.
Filter Data:
Set a filter on the Year column and select values greater than or equal to 2000.
Look for rows where Hindu - Total (Percent) has values.
Analyze Results: You can now visualize and calculate the growth of Hinduism worldwide after filtering out irrelevant data. Use statistical methods or graphical representations like line charts to understand trends over time.
Conclusion: This guide has provided you with an overview of how to use the Rel
- Comparing religious populations across different countries: With data available for different states and countries, this dataset allows for comparisons of religious populations across regions. Researchers can analyze how different religions are distributed geographically and compare their percentages or total populations across various locations.
- Studying the impact of historical events on religious demographics: Since the dataset includes records categorized by year, it can be used to study how historical events such as wars, migration, or political changes have influenced religious demographics over time. By comparing population numbers before and after specific events, resea...
Facebook
TwitterThe World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion.) Some of the religions are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided.
The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree we prepared a comprehensive literature review, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree.) The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases.
The National Religion Dataset: The observation in this dataset is a state-five-year unit. This dataset provides information regarding the number of adherents by religions, as well as the percentage of the state's population practicing a given religion.
Facebook
TwitterThe World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion.) Some of the religions (as detailed below) are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided.
The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree we prepared a comprehensive literature review, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree.) The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases.
The Global Religion Dataset: This dataset uses a religion-by-five-year unit. It aggregates the number of adherents of a given religion and religious group globally by five-year periods.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Pass Christian by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Pass Christian across both sexes and to determine which sex constitutes the majority.
Key observations
There is a slight majority of female population, with 52.36% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
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. No further analysis is done on the data reported from the Census Bureau.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Pass Christian Population by Race & Ethnicity. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Pass Christian population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Pass Christian across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Pass Christian was 6,255, a 1.97% increase year-by-year from 2022. Previously, in 2022, Pass Christian population was 6,134, an increase of 4.18% compared to a population of 5,888 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Pass Christian decreased by 363. In this period, the peak population was 6,950 in the year 2005. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Pass Christian Population by Year. You can refer the same here
Facebook
TwitterThe World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide from 1945 to 2010. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950,…, 2010). The data record percentages of the state’s population that practice a given religion. Some of the religions (as detailed in the Codebook) are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also specified in the Codebook.
The project was developed in three stages. The first stage consisted of the formation of a religions tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources, and imputing data for the missing cases.
Please see column description in the PDF file
Zeev Maoz and Errol A. Henderson. 2013. “The World Religion Dataset, 1945-2010: Logic, Estimates, and Trends.” International Interactions, 39: 265-291.
The WRP contains three datasets: the national religion dataset, the regional religion dataset, and the global religion dataset.
The National Religion Dataset. The unit of analysis in this dataset is the individual state, observed at five-year intervals. This dataset provides information regarding the number of adherents by religion, as well as the percent of the state’s population practicing a given religion.
The Regional Religion Dataset. The unit of analysis in this dataset is the region, observed at five-year intervals. This dataset utilizes the COW regional designations with one modification: the Oceania category for COW country code numbers 900 and above.
The Global Religion Dataset. The unit of analysis in this dataset is the global system, observed at five-year intervals. This dataset aggregates the number of adherents of a given religion and religious group for all states, globally.
Foto von James Coleman auf Unsplash
Facebook
Twitterhttps://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms
The CARPE project has been developed to empirically address the religious change and secularization debate. The present data set contains aggregate survey-based estimates for the proportion of persons attending church, according to various frequency/probability thresholds. Further variables are sample shares of denominations, proportion female, average respondent age, proportions of rough educational attainment groups, and identifiers for country, year, and survey programme. The pooled dataset involves 45 European countries and spans the years 1973 to 2016, with variable density of coverage across the countries. Those countries are Albania, Austria, Armenia, Belgium, Bosnia Herzegovina, Bulgaria, Belarus, Croatia, Cyprus, Northern Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Italy, Kosovo, Latvia, Lithuania, Luxembourg, Macedonia, Malta, Moldova, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Serbia, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom.
Estimates were derived from the individual-level data of the following survey programmes: • Eurobarometer (http://ec.europa.eu/public_opinion/), • European Social Survey (ESS), (http://www.europeansocialsurvey.org/), • European Values Study (EVS), (http://www.europeanvaluesstudy.eu/), • International Social Survey Programme (ISSP) (http://www.issp.org/), • World Values Survey (WVS) (http://www.worldvaluessurvey.org/)
Facebook
TwitterBy Correlates of War Project [source]
The World Religion Project (WRP) is an ambitious endeavor to conduct a comprehensive analysis of religious adherence throughout the world from 1945 to 2010. This cutting-edge project offers unparalleled insight into the religious behavior of people in different countries, regions, and continents during this time period. Its datasets provide important information about the numbers and percentages of adherents across a multitude of different religions, religion families, and non-religious affiliations.
The WRP consists of three distinct datasets: the national religion dataset, regional religion dataset, and global religion dataset. Each is focused on understanding individually specific realms for varied analysis approaches - from individual states to global systems. The national dataset provides data on number of adherents by state as well as percentage population practicing a given faith group in five-year increments; focusing attention to how this number evolves from nation to nation over time. Similarly, regional data is provided at five year intervals highlighting individual region designations with one modification – Pacific Ocean states have been reclassified into their own Oceania category according to Country Code Number 900 or above). Finally at a global level – all states are aggregated in order that we may understand a snapshot view at any five-year interval between 1945‐2010 regarding relationships between religions or religio‐families within one location or transnationally.
This project was developed in three stages: firstly forming a religions tree (a systematic classification), secondly collecting data such as this provided by WRP according to that classification structure – lastly cleaning the data so discrepancies may be reconciled and imported where needed with gaps selected when unknown values were encountered during collection process . We would encourage anyone wishing details undergoing more detailed reading/analysis relating various use applications for these rich datasets - please contact Zeev Maoz (University California Davis) & Errol A Henderson _(Pennsylvania State University)
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
The World Religions Project (WRP) dataset offers a comprehensive look at religious adherence around the world within a single dataset. With this dataset, you can track global religious trends over a period of 65 years and explore how they’ve changed during that time. By exploring the WRP data set, you’ll gain insight into cross-regional and cross-time patterns in religious affiliation around the world.
- Analyzing historical patterns of religious growth and decline across different regions
- Creating visualizations to compare religious adherence in various states, countries, or globally
- Studying the impact of governmental policies on religious participation over time
If you use this dataset in your research, please credit the original authors. Data Source
License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.
File: WRP regional data.csv | Column name | Description | |:-----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | Year | Reference year for data collection. (Integer) | | Region | World region according to Correlates Of War (COW) Regional Systemizations with one modification (Oceania category for COW country code ...
Facebook
Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains the estimated religious composition of 198 countries and territories for 2010 to 2050.
The data is sourced from PEW RESEARCH CENTER . In original dataset the number and the percentage share of followers for some religions as "<10000" and "<10%". Because of technical limitations of the visualization tool, these values had to be changed into "10000".
This file contains the number followers by religions and region for 2010 to 2050 | Column Name | Description | |-----------------|-------------------------------------------------------------------------------------------------| | Year | The year for which the data is recorded. | | Region | The region to which the country belongs. | | Country | The name of the country. | | Buddhists | The estimated number of Buddhists in the country for the given year. | | Christians | The estimated number of Christians in the country for the given year. | | Folk Religions | The estimated number of followers of folk religions in the country for the given year. | | Hindus | The estimated number of Hindus in the country for the given year. | | Jews | The estimated number of Jews in the country for the given year. | | Muslims | The estimated number of Muslims in the country for the given year. | | Other Religions | The estimated number of followers of other religions in the country for the given year. | | Unaffiliated | The estimated number of people with no religious affiliation in the country for the given year. |
This file contains the percentage share of followers by religions and region for 2010 to 2050 | Column Name | Description | |------------------|------------------------------------------------------------------------------------------------| | Year | The year for which the data is recorded. | | Region | The region to which the country belongs. | | Country | The name of the country. | | Christians | The percentage share of Christians in the country's population for the given year. | | Muslims | The percentage share of Muslims in the country's population for the given year. | | Unaffiliated | The percentage share of people with no religious affiliation in the country's population. | | Hindus | The percentage share of Hindus in the country's population for the given year. | | Buddhists | The percentage share of Buddhists in the country's population for the given year. | | Folk Religions | The percentage share of followers of folk religions in the country's population. | | Other Religions | The percentage share of followers of other religions in the country's population. | | Jews | The percentage share of Jews in the country's population for the given year. | | All Religions | The percentage share of all religious groups combined in the country's population for the year. |
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Pass Christian population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Pass Christian. The dataset can be utilized to understand the population distribution of Pass Christian by age. For example, using this dataset, we can identify the largest age group in Pass Christian.
Key observations
The largest age group in Pass Christian, MS was for the group of age 5-9 years with a population of 496 (8.77%), according to the 2021 American Community Survey. At the same time, the smallest age group in Pass Christian, MS was the 85+ years with a population of 67 (1.18%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Pass Christian Population by Age. You can refer the same here
Facebook
TwitterThis Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.
These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.
This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:
0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.
A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.
ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Pass Christian population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Pass Christian. The dataset can be utilized to understand the population distribution of Pass Christian by age. For example, using this dataset, we can identify the largest age group in Pass Christian.
Key observations
The largest age group in Pass Christian, MS was for the group of age 65 to 69 years years with a population of 547 (9.21%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Pass Christian, MS was the 85 years and over years with a population of 89 (1.50%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Pass Christian Population by Age. You can refer the same here
Facebook
TwitterData on religion by gender and age for the population in private households in Canada, provinces and territories.
Facebook
Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Null Hypotheses (H-not/H0) :- Are religious people more happy, and does it contribute to a better experience of life? ----------------------AND in the same vein ---------------------------------------------------------------------- Is the increasing trend of Atheism directly related to increasing reported levels of ADHD, depression and suicide rates around the world?
The research :- A slew of research suggests that religious people are happier, are better at keeping family ties, contribute to society more by being involved in the community, report better life experience and are better able to cope with life's setbacks like Divorce. Is this true? Below is a random list of research I found from googling :-
(1) https://www.psychologytoday.com/blog/more-mortal/201212/are-religious-people-happier-non-religious-people (2) https://www.psychologytoday.com/blog/curious/201510/does-being-religious-make-us-happy (3) http://www.huffingtonpost.co.uk/2016/02/02/office-for-national-statistics-well-being-data_n_9138076.html (4) https://www.unilad.co.uk/news/new-research-shows-religious-people-are-happier-than-atheists/ (5) https://www.christiantoday.com/article/why-religious-people-are-happier-and-how-to-share-the-joy/78581.htm (6) http://www.pewforum.org/2016/04/12/religion-in-everyday-life/
What the Quran says :- Having graduated from the London School of Economics (2004, Bsc Hons) and having been greatly influenced by Richard Dawkins, books like "The God Delusion" etc. for about 7 years and seeking extensively through the various religious/self development traditions including Judaism, Christianity, Buddhism, Hinduism, The Landmark Forum and Tai Chi, I converted to Islam 4 years ago. I can personally attest to having a much greater experience of life and feeling peace and tranquility and calmness in my heart. In the Sufi tradition, the heart is the kernel of connecting to God (Allah), and the seat of God consciousness :- https://www.youtube.com/watch?v=nqNPVP6GerM&index=1&list=PLwFLXkJiBtuza1uSJHsB8MJCfQ9l7h8jf
Allah says in the Quran :- "And whoever turns away from My remembrance - indeed, he will have a depressed life,...." [Quran 20:124]
And Allah also says in the Quran :- "Those who have believed and whose hearts are assured by the remembrance of Allah. Unquestionably, by the remembrance of Allah hearts are assured." [Quran 13:28]
Dataset :- The data set regarding population is the gross population by country taken from the World Bank Data Site, link here :- https://data.worldbank.org/indicator/SP.POP.TOTL?locations=US&view=chart
Can you :- Look at populations around the world using the dataset, and look at suicide levels, depression levels, reported ADHD levels, and anxiety levels and find a correlation between the increasing trend of atheism in the world and these reported markers.
Facebook
Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains religious distribution data for Pakistan from 1901 to 2023, sourced from various census data and official reports. The dataset provides a comprehensive overview of the population breakdown by religious groups across different decades. It includes historical data on major religions such as Islam, Hinduism, Sikhism, Christianity, and others, along with population percentages for each group at different points in time.
The dataset spans over a century and serves as a valuable resource for understanding the demographic and religious shifts in Pakistan's population. This data can be useful for researchers, policymakers, and educators interested in the sociological and historical trends of religious communities in Pakistan.
| Column Name | Description |
|---|---|
| Year | The census year corresponding to the data for that religious group |
| Religion_Pop | The total population of the religious group (e.g., Islam, Hinduism, Sikhism, Christianity) for the given year |
| Religious_% | The percentage of the religious group (e.g., Islam, Hinduism, Sikhism, Christianity) in relation to the total population |
This dataset is ideal for: - Studying demographic and religious trends in Pakistan - Researching the impact of religious distribution on social policies - Understanding historical changes in religious communities
Facebook
TwitterDonor rate and distribution of average annual donations, for the population aged 15 and over, by religious attendance, Canada and provinces.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Christian County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Christian County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2022, the population of Christian County was 33,436, a 0.85% decrease year-by-year from 2021. Previously, in 2021, Christian County population was 33,721, a decline of 0.67% compared to a population of 33,950 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Christian County decreased by 1,938. In this period, the peak population was 35,374 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Christian County Population by Year. You can refer the same here
Facebook
TwitterThis dataset provide a count of Veteran by their religious affiliation and state of residence. The dataset set covers all 50 states, District of Columbia and other territories.
Facebook
TwitterThis study, designed and carried out by the "http://www.asarb.org/" Target="_blank">Association of Statisticians of American Religious Bodies (ASARB), compiled data on 372 religious bodies by county in the United States. Of these, the ASARB was able to gather data on congregations and adherents for 217 religious bodies and on congregations only for 155. Participating bodies included 354 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao, Zoroastrian, American Ethical Union, and National Spiritualist Association congregations, and counts of congregations and adherents from Baha'i, three Buddhist groupings, two Hindu groupings, four Jewish groupings, and Muslims. The 372 groups reported a total of 356,642 congregations with 161,224,088 adherents, comprising 48.6 percent of the total U.S. population of 331,449,281. Membership totals were estimated for some religious groups.
In January 2024, the ARDA added 21 religious tradition (RELTRAD) variables to this dataset. These variables start at variable #12 (TOTCNG_2020). Categories were assigned based on pages 88-94 in the original "https://www.usreligioncensus.org/index.php/node/1638" Target="_blank">2020 U.S. Religion Census Report.
Visit the "https://www.thearda.com/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data sources.
Facebook
TwitterBy Throwback Thursday [source]
The dataset contains information on a wide range of religions, including Christianity, Judaism, Islam, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism, Zoroastrianism, Syncretic Religions (religious practices that blend elements from multiple faiths), Animism (belief in spiritual beings in nature), Non-Religious individuals or those without any religious affiliation.
For each religion and region/country combination recorded in the dataset we have the following information:
- Total population: The total population of the region or country.
- Religious affiliation percentages: The percentages of the population that identify with specific religious affiliations.
- Subgroup populations/percentages: The populations or percentages within specific denominations or sects of each religion.
The dataset also provides additional variables like Year and State Name (for regional data) for further analysis.
Understanding the Columns
The dataset contains several columns with different categories of information. Here's a brief explanation of some important columns:
- Year: The year in which the data was recorded.
- Total Population: The total population of a country or region.
- State Name (StateNme): The name of the state or region.
Each religion has specific columns associated with it, such as Christianity, Buddhism, Islam, Hinduism, Judaism, Taoism, Shintoism etc., representing its percentage and population for each category/denomination within that religion.
Selecting Specific Data
If you are interested in exploring data related to a particular religion or geographic location:
To filter data by Religion: Identify relevant columns associated with that religion such as 'Christianity', 'Buddhism', 'Islam', etc., and extract their respective percentage and population values for analysis.
Example: If you want to analyze Christianity specifically, extract columns related to Christianity like 'Christianity (Percent)', 'Christianity (Population)', etc.
Note: There might be multiple columns related to a specific religion indicating different categories or denominations within that religion.
To filter data by Geographic Location: Utilize the 'State Name' column ('StateNme') to segregate data corresponding to different states/regions.
Example: If you want to analyze religious demographics for a particular state/region like California or India:
i) Filter out rows where State Name is equal to California or India.
ii) Extract relevant columns associated with your selected religion as mentioned above.
Finding Trends and Insights
Once you have selected the specific data you are interested in, examine patterns and trends over time or across different regions.
Plotting data using visualizations: Use graphical tools such as line charts, bar charts, or pie charts to visualize how religious demographics have changed over the years or vary across different regions.
Analyzing population proportions: By comparing the percentage values of different religions for a given region or over time, you can gather insights into changes in religious diversity.
Comparing Religions
If you wish to compare multiple religions:
- Comparing religious affiliations across different countries or regions: With data on various religions such as Christianity, Islam, Buddhism, Judaism, Hinduism, etc., researchers can compare the religious affiliations of different countries or regions. This can help in understanding the cultural and religious diversity within different parts of the world.
- Exploring the growth or decline of specific religions: By examining population numbers for specific religions such as Jainism, Taoism, Zoroastrianism, etc., this dataset can be used to investigate the growth or decline of these religious groups over time. Researchers can analyze factors contributing to their popularity or decline in particular regions or countries
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: ThrowbackDataThursday 201912 - Religion.csv | Column name...