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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of ... in that feedback from later phases may result in additional work in earlier ... Qualitative research; Structured data analysis ...

  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. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    To create a synthetic data point, take the vector between one of those k neighbors, and the current data point. Multiply this vector by a random number x which lies between 0, and 1. Add this to the current data point to create the new, synthetic data point. Many modifications and extensions have been made to the SMOTE method ever since its ...

  5. Research - Wikipedia

    en.wikipedia.org/wiki/Research

    The researcher(s) collects data to test the hypothesis. The researcher(s) then analyzes and interprets the data via a variety of statistical methods, engaging in what is known as empirical research. The results of the data analysis in rejecting or failing to reject the null hypothesis are then reported and evaluated.

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data scientists often work with unstructured data such as text or images and use machine learning algorithms to build predictive models and make data-driven decisions. In addition to statistical analysis, data science often involves tasks such as data preprocessing, feature engineering, and model selection.

  7. Empirical research - Wikipedia

    en.wikipedia.org/wiki/Empirical_research

    Accurate analysis of data using standardized statistical methods in scientific studies is critical to determining the validity of empirical research. Statistical formulas such as regression, uncertainty coefficient, t-test, chi square, and various types of ANOVA (analyses of variance) are fundamental to forming logical, valid conclusions.