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Why data collection and data analysis should not be separated at the planning stage of any research project?
The question is utter nonsense! There are plenty of instances in which research is carried out on secondary data - these are data that have been collected by some other body. For example, if you were doing an analysis to examine any relationship between different countries' haul of Olympic medals and their GDP, you would not even do the data collection. You would use published data on GDP and on past medal hauls.
What is the difference 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
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.
How does technical analysis differ from the fundamental analysis?
Technical vs. fundamental analysisThe primary difference can be summed up in terms of both the underlying philosophy, and the data studied. Fundemental analysis is concerned chiefly with discovering asset values. The data relied upon includes off exchange sources such as balance sheets, income statements and supply and demand statistics.Technical analysis on the other hand, is concerned chiefly with the timing of buy and sell decisions. The data studied is generated exclusively by the exchanges.Where does investor sentiment fall within these two definitions? If the sentiment data is derived from options data, then it would fit the definition of technical analysis. If on the other hand the data was generated by opinion polls, then it would not fit the definition of technical analysis. Nor would it be considered fundamental analysis either. It would more properly and simply be defined as "sentiment analysis."While there is some debate over whether off-exchange data (e.g. astrological data, dividends, opinion polls, etc.) properly belong under the definition of technical analysis, none of the main organizing bodies for technical analysis have ever rendered an official, public opinion on this question.According to noted technical analyst Daniel Chesler, CMT --"Technical analysis is the forecasting of markets through the study and analysis of data generated exclusively from the buying and selling of financial instruments. It is part science and part formalization of trader intuition and experience. Any market for which there is a regular, transparent transaction history is a candidate for technical analysis. Planetary cycles, opinion polls, fundamental, monetary and economic data as well as any data not specifically generated from the buying and selling process, are not a part of orthodox technical analysis."
What are primary and secondary research?
From my understanding, Primary and Secondary research are the difference in conducting the research. In Primary research, there is no data available for the researcher, hence the researcher has to start from scratch. This means that the researcher needs to design questionaires, collect data from respondents and then analyse the result. If you are doing secondary research, the researcher have the necessary data available. These data are made available through other publications or reports, like newspaper or annual reports of companies. If the researcher is doing secondary research, there is no need to start from scratch, he or she uses the data or information done by other organizations or publications. The important thing is that there are advantages and disadvantages for both methods. Primary research is more time consuming and costly. While some secondary research may not suit the researcher's needs.
How is research conducted for PR?
Survey questionnaires and structured interviews are useful methods of collecting data for analysis of the potential market. In some cases, information is taken from secondary data, that is, data collected and published by others.(Ex: government agencies)
What is data analysis and discussion mean?
Data analysis and discussion means when your talking with some one and talking about something
Why data collection and data analysis should not be separated at the planning stage of any research project?
The question is utter nonsense! There are plenty of instances in which research is carried out on secondary data - these are data that have been collected by some other body. For example, if you were doing an analysis to examine any relationship between different countries' haul of Olympic medals and their GDP, you would not even do the data collection. You would use published data on GDP and on past medal hauls.
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.
Two example of secondary and primary data?
Two examples of primary data are survey responses collected directly from individuals and experiments conducted to gather specific data. Two examples of secondary data are data obtained from government reports and data collected from previous research studies.
What is the difference 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
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.
What are some solutions to barriers of communication?
about the barriers of communication about the barriers of communication
What are the Tools and techniques of Data analysis?
There are several data analysis tools on the market, each with its own set of features. The choice of tool should always be based on the type of analysis being performed and the type of data being processed. Here is a list of some interesting data analysis tools. Excel, Tableau, Power BI, Smooth Reports, R & Python, SAS. Data analysis depends on the questions, the type of data and the amount of data collected. Each is about gathering new data, uncovering insights, and digging for deeper information to turn facts and figures into decision-making parameters. Thus, various data analysis techniques can be categorized as follows: Engineering based on mathematics and statistics Techniques based on artificial intelligence and machine learning Techniques based on visualization and graphics SPSS is also used to perform a variety of data analyses and tests. SPSS makes this type of data analysis easier for researchers. You can check some professional websites like SPSS-Tutor, and SilverLake Consult where you will find many important types of analysis which are performed by using SPSS. In fact, you can contact them to know in-depth about SPSS.
What are some examples of natural barriers?
Oceans are some of the natural barriers in the planet.
How information can change into data?
To convert data into information, you must perform some summarization, analysis, and interpretation. Data doesn't allow one to make decisions or inferences, but information does.
How do you write a data analysis for a science project?
Take some time to carefully review all of the data you have collected from your experiment. Use charts and graphs to help you analyze the data and patterns.
