Secondary Data
Definition and Types of Secondary Data
Secondary data refers to data that was collected by someone other than the user. Common sources of secondary data for social science include censuses, information collected by government departments, organizational records and data that was originally collected for other research purposes.
Secondary data falls into two categories: internal and external. Internal secondary data is data that have been collected within the researcher's own organization or that relate to the researcher's customers. This data may be documented, hidden or stored within the organization's files, or may be available on the organization's website.
External secondary data, on the other hand, is data that has been published by other organizations, such as the government, trade associations, or scientific research institutions. This type of data can be in the form of 'raw' data, or compiled and processed statistical data.
Advantages and Disadvantages of Secondary Data
Secondary data analysis can save time that would otherwise be spent collecting data and, particularly in the case of quantitative data, can provide larger and higher-quality databases that would be unfeasible for any individual researcher to collect on their own. Furthermore, those researchers and institutions who have access to large databases may be unwilling to share this data with others, given the time, effort and financial resources that went into collecting it.
However, secondary data analysis can also present several challenges. The most significant of these are issues related to the validity and reliability of the data. Since the researcher did not collect the data, they can only make an educated guess about the accuracy of the data. Furthermore, the data may be outdated or may not accurately represent the population the researcher is interested in studying.
Methods of Secondary Data Collection
Secondary data can be collected in a number of ways, including through document analysis, content analysis, or through the re-analysis of existing statistical data. Document analysis involves the study of existing documents, whether in the form of public records, private records, or archives. Content analysis, on the other hand, involves the study of specific aspects of recorded communication, such as a transcript of a political speech or a series of newspaper articles.
Re-analysis of existing statistical data involves the use of statistical techniques to interpret data that was previously collected by others. This can involve the use of simple descriptive statistics, such as averages and measures of dispersion, or more complex inferential statistics, such as regression analysis.
Applications of Secondary Data
Secondary data is used in a wide variety of fields, including sociology, economics, political science, and public health. In sociology, for example, researchers may use secondary data to examine social trends over time or to compare social behaviors in different countries. In economics, secondary data can be used to study economic trends or to compare the economic performance of different countries. In political science, secondary data may be used to study voting behavior or to compare political systems in different countries. In public health, secondary data can be used to identify risk factors for disease or to evaluate the effectiveness of health interventions.
Conclusion
In conclusion, secondary data is a valuable resource for researchers in a variety of fields. Despite the potential challenges associated with its use, secondary data can provide a wealth of information that would be difficult, if not impossible, to collect in any other way.