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  2. Data collection - Wikipedia

    en.wikipedia.org/wiki/Data_collection

    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 answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business ...

  3. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Different companies or organizations hold data analysis contests to encourage researchers to utilize their data or to solve a particular question using data analysis. [151] [152] A few examples of well-known international data analysis contests are as follows: [153] Kaggle competition, which is held by Kaggle. [154]

  4. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data analysis typically involves working with smaller, structured datasets to answer specific questions or solve specific problems. This can involve tasks such as data cleaning, data visualization, and exploratory data analysis to gain insights into the data and develop hypotheses about relationships between variables. Data analysts typically ...

  5. Analytical skill - Wikipedia

    en.wikipedia.org/wiki/Analytical_skill

    It is a tool to discover and decipher useful information for business decision-making. It is imperative in inferring information from data and adhering to a conclusion or decision from that data. Data analysis can stem from past or future data. Data analysis is an analytical skill, commonly adopted in business, as it allows organisations to ...

  6. Scientific method - Wikipedia

    en.wikipedia.org/wiki/Scientific_method

    Research questions, the collection of data, or the interpretation of results, all are subject to larger amounts of scrutiny than in comfortably logical environments. Statistical models go through a process for validation , for which one could even say that awareness of potential biases is more important than the hard logic; errors in logic are ...

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    While the tools of data analysis work best on data from randomized studies, they are also applied to other kinds of data—like natural experiments and observational studies [19] —for which a statistician would use a modified, more structured estimation method (e.g., difference in differences estimation and instrumental variables, among many ...

  8. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    The interpretation of a p-value is dependent upon stopping rule and definition of multiple comparison. The former often changes during the course of a study and the latter is unavoidably ambiguous. (i.e. "p values depend on both the (data) observed and on the other possible (data) that might have been observed but weren't"). [69]

  9. 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.