Applications Of Quantitative Secondary Data Analysis – Step By Step Guide

A research process known as secondary analysis uses extant data to examine new topics or to confirm the conclusions of the earlier study. Although it can be used with both quantitative and qualitative data, the former is where it is more well-established. Our main focus will, however, be quantitative secondary data analysis. Primary data are those that researchers have personally acquired, whereas secondary data are those that have been gathered by someone else.

Sources Of Secondary Data:

  • national, state, or municipal government reports
  • reports from foreign governments and international businesses
  • books, periodicals, and journals
  • publications from academic institutions, research organizations, and researchers

Significance Of Secondary Data:

Secondary data is typically out of date because it is linked to events that have already occurred. Therefore, the researcher must consider the date of data collection, the time between data collection and release, and the data’s applicability to current circumstances.

Benefits Of Secondary Data Analysis:

  • The ability to save money is the main benefit of using secondary data.
  • The researcher does not need to invest time, money, resources, or effort into gathering the data because it has already been done.
  • The secondary data collection may occasionally need to be acquired. Still, the price is nearly always less than the cost of gathering a comparable data set from scratch, which typically includes salaries, travel and lodging expenses, office expenditures, equipment purchases, and other overhead expenses.
  • Additionally, since the data has already been gathered, often cleansed, and saved electronically, the researcher can focus more on analysis than on preparing the data
  • The available range of data is a second significant benefit of employing secondary data.
  • Numerous large-scale, national investigations are carried out by the federal government that would be challenging for independent researchers to gather data from.
  • Many of these data sets are also longitudinal, which means that the same population’s data was gathered over several distinct time periods. This makes it possible for researchers to examine patterns and evolution of events throughout time.
  • The fact that secondary data collecting frequently retains a level of professionalism and skill that may not be present with lone researchers or small research projects is a third significant benefit of using secondary data.

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Applications Of Quantitative Secondary Data Analysis:

A step-by-step application of Quantitative Secondary Data Analysis is given below:

Determine The Research Question:

Science and technology are working every day to widen the boundaries of knowledge and information. And not just science but every field is trying to explore more and more every day. By performing quantitative secondary data analysis, scientists and researchers can raise and find solutions to more research questions.

Devise A Plan For Addressing The Research Topic And Finding Solutions:

After determining the research question, the researchers devise a plan to analyze the primary research. This plan determines:

  • Who will be included in the research team?
  • What kind of primary research is to be analyzed to solve the research problem of interest?
  • What will be the pattern of analysis?

A plan is thus devised and the research is conducted.

Analyse The Primary Data:

The primary data of interest is analyzed. If fortunately, the quantitative secondary data analysis goes well and the research is successful, the research problem can be solved.

Create/Gather A Sample:

The findings of quantitative secondary data analysis (or the solution to the problem) are then ready to be tested. For testing, a sample is prepared. The sample is prepared according to the problem. It can be abiotic (water, air, soil, etc.) or biotic (mammals, birds, insects, bacteria, fungus, viruses, etc.) depending upon the research problem.

Conduct Tests:

A series of tests are conducted on the sample and the results are illustrated and examined by the experts.

Verifying The Findings Of Qualitative Research:

After conducting a series of tests, the results are verified by the experts as positive or negative.


The research conducted by using the technique of quantitative secondary data analysis is then published so that the research problem can be addressed globally. By following this guide, you can conduct an efficient quantitative secondary data analysis.

Assessing Secondary Data:

As with any main data, the researcher must approach the secondary data with caution. He must determine whether he has access to the data and whether the secondary data that is readily available will help him reach his study goals.


It is vital to assess the secondary data in light of the approach used to get it. Therefore, the researcher must assess variables including:

  1. sampling strategy
  2. sample size
  3. response rate
  4. fieldwork processes
  5. data processing techniques


The researcher should evaluate the accuracy of the data from the secondary source to ensure the validity of his study. The researcher won’t receive a detailed explanation of the methodology or standards, though. As a result, determining the accuracy of secondary data is sometimes exceedingly difficult. However, the correctness might be verified by the researcher through triangulation research.

Data Collection Date:

Secondary data is typically out of date since it is linked to events that have previously occurred. Therefore, the researcher must consider the date of data collection, the time between data collection and release, and the data’s applicability to current circumstances. Since census data is only gathered once every few years, the timing of data collection is the main problem.

The Reason For Collecting Data:

Once more, secondary data is defined as information that was gathered for purposes or goals unrelated to those of the researcher or consultant who is currently analyzing it. The extent to which data gathered with another goal or specific target in mind is suitable and relevant to the researcher’s condition or problem must be determined by the researcher.

Data’s Content:

High validity and accuracy data cannot be of any benefit if the data’s substance is subpar.

There may not always be a direct connection between the measuring categories used by the researcher and the correlations evaluated by the data. The information may, for instance, take into account the connection between motivation and wage levels. However, the researcher who is using secondary data to gauge motivation may have defined and measured motivation in a way that is incongruent or improper.

Source Credibility:

It is advised that while assessing secondary data resources, the researcher should take into account aspects like:

  1. competence
  2. credibility
  3. overall source trustworthiness

Government reports are often seen as having higher credibility than other commercial sources of secondary data.


Quantitative Secondary Data Analysis is easy and comparatively less expensive to conduct and yet, can be very useful. If you have read the guidelines and precautions properly then you can undoubtedly conduct a productive Quantitative Secondary Data Analysis.

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