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What is existing statistics?
secondary data source on which you rely on what other people have already published about the topic at hand.
What are the method of data collection in statistics?
In statistics, data collection methods can be broadly categorized into primary and secondary methods. Primary data collection involves gathering new data directly from sources through techniques such as surveys, experiments, interviews, and observations. Secondary data collection, on the other hand, involves analyzing existing data that has been previously collected, such as databases, reports, and academic papers. Both methods aim to ensure data is accurate, reliable, and relevant to the research question at hand.
What are the different between primary data and secondary data?
Primary data is data which has been collected by yourself, which is more reliable and up to date. Secondary data has been collected from a secondary source (Other people, business etc.) so it may not be valid or up to date."Primary" and "secondary" are terms used to define data relative to the purpose by which the data were collected originally."Primary data" are data collected for the need at hand."Secondary data" are data that were collected for another reason but is being re-purposed to address the need at hand.When describing the expertise of data analysts, it is not uncommon to distinguish between primary and secondary data analytics. Primary data analytics involves the ability to analyze data for the purpose by which it has been collected. Secondary data analytics involves identifying "secondary data sources" to solve a new problem and then the ability to re-purpose that data.Primary data is a data which is created for the first time and there is no previous source available. Secondary data is a readily available data like data from trade directories,statistics from websites etc. In Dissertation Literature review is done through secondary data which includes the contents such as theories, models, compilation, research findings by some other scholar etc.
3 ways of presenting data in statistics?
ways of presenting data in statistics
Why it is said all statistics are data but all data are not statistics?
All statistics are data because all statistics are formed of numbers and numbers are a type of data (numrical). But not all data is statistics because not all data is numbers, it can also be words, pictures etc. It's like saying all apples are fruit but all fruit are not apples.
What is existing statistics?
secondary data source on which you rely on what other people have already published about the topic at hand.
What are the method of data collection in statistics?
In statistics, data collection methods can be broadly categorized into primary and secondary methods. Primary data collection involves gathering new data directly from sources through techniques such as surveys, experiments, interviews, and observations. Secondary data collection, on the other hand, involves analyzing existing data that has been previously collected, such as databases, reports, and academic papers. Both methods aim to ensure data is accurate, reliable, and relevant to the research question at hand.
Types of secondary data?
Some common types of secondary data include statistics, company reports, academic papers, government publications, and market research reports. These sources are typically collected by other individuals or organizations and can be used to support research, analysis, or decision-making.
What are the merits and demerits of primary and secondary source of data in statistics?
Reliable and comprehensive statistics can be very expensive to collect and process. You may not have the authority to force compliance and so your data may have serious gaps. These pitfalls can be avoided if there are suitable secondary statistics that have already been compiled. However, you may not know exactly how the statistics were compiled and processed so may not fully know what they represent. Also, they may not measure exactly what you want or may not be based on the exact target population. These demerits can be overcome by collecting the statistics yourself.
What are difference between primary and secondary data?
Primary data is data which has been collected by yourself, which is more reliable and up to date. Secondary data has been collected from a secondary source (Other people, business etc.) so it may not be valid or up to date."Primary" and "secondary" are terms used to define data relative to the purpose by which the data were collected originally."Primary data" are data collected for the need at hand."Secondary data" are data that were collected for another reason but is being re-purposed to address the need at hand.When describing the expertise of data analysts, it is not uncommon to distinguish between primary and secondary data analytics. Primary data analytics involves the ability to analyze data for the purpose by which it has been collected. Secondary data analytics involves identifying "secondary data sources" to solve a new problem and then the ability to re-purpose that data.Primary data is a data which is created for the first time and there is no previous source available. Secondary data is a readily available data like data from trade directories,statistics from websites etc. In Dissertation Literature review is done through secondary data which includes the contents such as theories, models, compilation, research findings by some other scholar etc.
What are the different between primary data and secondary data?
Primary data is data which has been collected by yourself, which is more reliable and up to date. Secondary data has been collected from a secondary source (Other people, business etc.) so it may not be valid or up to date."Primary" and "secondary" are terms used to define data relative to the purpose by which the data were collected originally."Primary data" are data collected for the need at hand."Secondary data" are data that were collected for another reason but is being re-purposed to address the need at hand.When describing the expertise of data analysts, it is not uncommon to distinguish between primary and secondary data analytics. Primary data analytics involves the ability to analyze data for the purpose by which it has been collected. Secondary data analytics involves identifying "secondary data sources" to solve a new problem and then the ability to re-purpose that data.Primary data is a data which is created for the first time and there is no previous source available. Secondary data is a readily available data like data from trade directories,statistics from websites etc. In Dissertation Literature review is done through secondary data which includes the contents such as theories, models, compilation, research findings by some other scholar etc.
3 ways of presenting data in statistics?
ways of presenting data in statistics
What are cases in statistics?
In statistics, cases are comprised of the data that is being studies. The cases in statistics can be updated frequently as the data changes.
The classification and collection of data that are in the form of numbers is called?
Statistics
What is external secondary data?
External secondary data - data that is obtained outside the firm itself.
How many churches are there in Oxford?
Data gathered from official Statistics Some important notes: - The data for England includes both Maintained (state) and Independent (private) schools - In Scotland, Wales and Northern Ireland, the Independent Schools are counted separately, but the statistics make no distinctions between primary and secondary Independent Schools ---- Data as of January 2006 Primary Schools (includes Middle Schools as deemed): 17,504 Secondary Schools (includes Middle Schools as deemed): 3,367 Data as of 2005 Primary Schools: 2,194 Secondary Schools: 385 Independent Schools: 152 Data as of 2004/2005 Primary Schools: 1,572 Secondary Schools: 227 Independent Schools: 58 Data as of 2005/2006 Primary Schools: 886 Secondary (non grammar) Schools: 161 Grammar Schools: 69 Independent Schools: 19
What are descriptive statistics and inferential statistics?
Descriptive statistics is a summary of data. Inferential statistics try to reach conclusion that extend beyond the immediate data alone.
