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Secondary data generally have a pre-established degree of validity and reliability which need not be re-examined by the researcher who is re-using such data. Secondary data is key in the concept of data enrichment, which is where datasets from secondary sources are connected to a research dataset to improve its precision by adding key ...
Secondary research is based on already published data and information gathered from other conducted studies. [8] It is a common practice by researchers to conduct secondary research before primary research in order to determine what information is not already available. [9]
Primary, or "statistical" sources are data that are collected primarily for creating official statistics, and include statistical surveys and censuses. Secondary, or "non-statistical" sources, are data that have been primarily collected for some other purpose (administrative data, private sector data etc.).
Secondary data is data that already exists, such as census data, which can be re-used for the research. It is good ethical research practice to use secondary data wherever possible. [44] Mixed-method research, i.e. research that includes qualitative and quantitative elements, using both primary and secondary data, is becoming more common. [45]
Secondary analysis of quantitative data is relatively widespread in comparative research, undoubtedly in part because of the cost of obtaining primary data for such large things as a country's policy environment. This study is generally aggregate data analysis. Comparing large quantities of data (especially government sourced) is prevalent. [4]
A secondary source usually provides analysis, commentary, evaluation, context, and interpretation. It is this act of going beyond simple description, and telling us the meaning behind the simple facts, that makes them valuable to Wikipedia. Reputable secondary sources are usually based on more than one primary source.
Depending on the topic of research, a scholar may use a bibliography, dictionary, or encyclopedia as either a tertiary or a secondary source. [1] This causes some difficulty in defining many sources as either one type or the other. In some academic disciplines, the differentiation between a secondary and tertiary source is relative. [1] [3]
In medical research, epidemiology, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data. [definition needed]