A research process known as secondary analysis uses existing 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:

Because secondary data is connected to past events, it is frequently out-of-date. As a result, the researcher must take into account the date of data collection, the interval between data collection and publication, and if the data apply to the current situation. A good masters dissertation help provider company can be hired for effective data collection.

Benefits of Secondary Data Analysis:

• The ability to save money is the main benefit of using secondary data.
• The data collection process has already been completed; therefore, the researcher does not need to expend any additional time, money, resources, or effort.
• Although it might occasionally be necessary to acquire secondary data collection, the cost is almost always less than what it would be to compile a comparable data set from scratch, which would typically involve paying salaries, travel and lodging costs, office costs, and equipment purchases, and other overhead costs.
• Additionally, the researcher can concentrate more on analysis than data preparation because the data has already been collected, often cleaned, and preserved electronically.
• An important advantage of using secondary data is the variety of data that is readily available.
• The federal government conducts numerous extensive, nationwide investigations that would be difficult for independent researchers to collect data from.
• The fact that many of these data sets are longitudinal indicates that information about the same population was acquired over a number of different time periods. Researchers are now able to look for patterns and the development of historical events.
• An important advantage of adopting secondary data is that it frequently preserves a level of expertise and ability that may not be present with lone researchers or small research efforts.

Applications of Quantitative Secondary Data Analysis:

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

1. 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.

2. 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?

3. 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.

4. 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.

5. Conduct Tests:

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

6. Verifying the Findings of Qualitative Research:

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

7. Publication:

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.

1. Methodology:

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

2. Error/Accuracy:

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.

3. Data Collection Date:

Since secondary data is connected to past events, it frequently contains outdated information. As a result, the researcher must take into account the date of data collection, the interval between data collection and publication, and if applicable to the current situation. The timing of data collection is the key issue because the census is only conducted once every few years.

4. The Reason for Collecting Data:

Reiterating the definition from earlier, secondary data is described as information that was obtained for objectives or goals distinct from those of the researcher or consultant who is currently studying it. The researcher must decide to what extent data collected with another purpose or specific target in mind is appropriate and relevant to the researcher’s condition or problem.

5. 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, it’s possible that the researcher who is analyzing secondary data did not define or assess motivation in a way that is appropriate or congruent.

6. 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 reliability of the source

Compared to other commercial sources of secondary data, government reports are frequently thought to have a higher level of reliability.

Conclusion:

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.