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Secondary data refers to data that is collected by someone other than the primary user. [1] 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. [ 2 ]
Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). [4]
A secondary analysis of the data from a planned study uses tools from data analysis, and the process of doing this is mathematical statistics. Data analysis is divided into: descriptive statistics – the part of statistics that describes data, i.e. summarises the data and their typical properties.
Common examples of secondary research include textbooks, encyclopedias, news articles, review articles, and meta analyses. [2] [3] When conducting secondary research, authors may draw data from published academic papers, government documents, statistical databases, and historical records. [1] [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.
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Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines , from the physical and social sciences to the humanities ; it is also used and misused for making informed decisions in all areas of business and government .
In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]