Secondary Data Analysis Dissertation
Secondary analysis is usually contrasted with primary analysis, which is the analysis of primary data independently collected by a researcher.Unlike primary data, which is collected by a researcher herself in order to fulfill a particular research objective, secondary data is data that was collected by other researchers who likely had different research objectives. and around the world collect data that they make available for secondary analysis.She should also consider whether the data must be adapted or adjusted in some way prior to her conducting her own analysis.Qualitative data is usually created under known circumstances by named individuals for a particular purpose.Sometimes researchers or research organizations share their data with other researchers in order to ensure that its usefulness is maximized. In many cases, this data is available to the general public, but in some cases, it is only available to approved users. Census, the General Social Survey, and the American Community Survey are some of the most commonly used secondary data sets within the social sciences.Secondary data can be both quantitative and qualitative in form. In addition, many researchers make use of data collected and distributed by agencies including the Bureau of Justice Statistics, the Environmental Protection Agency, the Department of Education, and the U. Bureau of Labor Statistics, among many others at federal, state, and local levels.This form of secondary analysis is also called Secondary data represents a vast resource to sociologists. It can include information about very large populations that would be expensive and difficult to obtain otherwise.Additionally, secondary data is available from time periods other than the present day.
As a research method, it saves both time and money and avoids unnecessary duplication of research effort.
The secondary data are readily available from the other sources and as such, there are no specific collection methods.
The researcher can obtain data from the sources both internal and external to the organization.
This makes it relatively easy to analyze the data with an understanding of biases, gaps, social context, and other issues.
Quantitative data, however, may require more critical analysis.