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  2. Data management plan - Wikipedia

    en.wikipedia.org/wiki/Data_management_plan

    A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; [2] this may lead to data being well-managed in the present ...

  3. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  5. Clinical data management - Wikipedia

    en.wikipedia.org/wiki/Clinical_data_management

    The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure

  6. Research design - Wikipedia

    en.wikipedia.org/wiki/Research_design

    A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...

  7. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    Collecting data from numerous sources and analyzing it using different data analysis tools has its advantages, including overcoming the risk of method bias; using data from different sources and analyzing it using multiple analysis methods guarantees businesses and organizations robust and reliable findings they can use in decision making.

  8. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Another way to prevent this is taking a double-blind design to the data-analysis phase, making the study triple-blind, where the data are sent to a data-analyst unrelated to the research who scrambles up the data so there is no way to know which participants belong to before they are potentially taken away as outliers. [25]

  9. Quantitative research - Wikipedia

    en.wikipedia.org/wiki/Quantitative_research

    Quantitative research using statistical methods starts with the collection of data, based on the hypothesis or theory. Usually a big sample of data is collected – this would require verification, validation and recording before the analysis can take place. Software packages such as SPSS and R are typically used for this purpose. Causal ...