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Big data in health research is particularly promising in terms of exploratory biomedical research, as data-driven analysis can move forward more quickly than hypothesis-driven research. [88] Then, trends seen in data analysis can be tested in traditional, hypothesis-driven follow up biological research and eventually clinical research.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
Example of data collection in the biological sciences: Adélie penguins are identified and weighed each time they cross the automated weighbridge on their way to or from the sea. [1] Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to ...
The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...
The main academic full-text databases are open archives or link-resolution services, although others operate under different models such as mirroring or hybrid publishers. . Such services typically provide access to full text and full-text search, but also metadata about items for which no full text is availa
Research data archiving is the long-term storage of scholarly research data, including the natural sciences, social sciences, and life sciences.The various academic journals have differing policies regarding how much of their data and methods researchers are required to store in a public archive, and what is actually archived varies widely between different disciplines.
A considerable amount of data quality research involves investigating and describing various categories of desirable attributes (or dimensions) of data. Nearly 200 such terms have been identified and there is little agreement in their nature (are these concepts, goals or criteria?), their definitions or measures (Wang et al., 1993).