Less Time Taking
Secondary Quantitative data research takes less time to be collected as it is already present because of the primary research.
Secondary Quantitative analysis or just secondary data research includes the analysis and evaluation of the data that has already been collected by some other researcher.
The re-analysis is generally based on some different research which can use the same data or a part of the data collected earlier. The researcher in the secondary data analysis is less involved in the research work as compared to the researcher who collected the primary data.
The data collection process in the primary research can include a lot of data which was not used properly. It could be because of time variants or the research limitations too. This is why the secondary research takes place to go through the other data thoroughly in the new research.
Our experts are experienced in the field and understand what type of data is suitable for specific research. After discussing with you the needs and requirements of the project, our team starts collecting the data from reliable past research and then thoroughly analyses and interprets it to see whether the collected data fits in the secondary research context.
Not just that but our team constantly stays in contact with the candidate to provide them updates and make changes(if any) on-time.
Moreover, the assembling of data and format checks go through several parameters to make sure that it is according to the demand of the project.
Why is Secondary Quantitative Research better?
Secondary Quantitative data research takes less time to be collected as it is already present because of the primary research.
It does not start by searching from the scratch which is why it is less time consuming than the time taken for primary data collection.
The data has been already used for some research earlier and thus, it is already organized in an understandable way.
The good organization of the primary data makes it easier to analyse for the secondary research as there is no such confusion in interpreting.
The quantitative data has numbers and proofs supporting the base which makes sure to set reliability in the facts it points.
With the primary data already at hand, the researcher can start planning and strategizing directly how it can be used for secondary quantitative data analysis without mistakes.
Dissertation Singapore uses different approaches and statistical tools to get the best output. Some of these tools include ANOVA, NVivo, Independent t-test and Chi-Square test. Not just these but our data analysts are also familiar with statistical tools like SPSS, SAS, STATA, R, AMOS and so on.
These tools allow us to smoothly organize the data collected and put it in the format as per the requirement within the service deadline.
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With us you can rest assured about the quality as our experts provide services based on the standards set by the rubric metrics and topping the score scale.
For further details, get in contact with us and let our team explain the process to you.