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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that is aimed at answering the original research question. [109] The initial data analysis phase is guided by the following four questions: [110]

  3. Why data analysis is going to be necessary for your job - AOL

    www.aol.com/finance/why-data-analysis-going...

    Data analytics is already changing how we do business, and experts believe this trend will accelerate. The three primary methods of business analytics are descriptive, predictive, and prescriptive

  4. Analytical skill - Wikipedia

    en.wikipedia.org/wiki/Analytical_skill

    Using data analysis as an analytical skill means being able to examine large volumes of data and then identifying trends within the data. It is critical to be able to look at the data and determine what information is important and should be kept and what information is irrelevant and can be discarded. [45] Data analysis includes finding ...

  5. 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 ...

  6. Critical data studies - Wikipedia

    en.wikipedia.org/wiki/Critical_data_studies

    First, 'big data' is an important aspect of twenty-first century society, and the analysis of 'big data' allows for a deeper understanding of what is happening and for what reasons. [1] Big data is important to critical data studies because it is the type of data used within this field.

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    When full census data cannot be collected, statisticians collect sample data by developing specific experiment designs and survey samples. Statistics itself also provides tools for prediction and forecasting through statistical models. To use a sample as a guide to an entire population, it is important that it truly represents the overall ...

  8. 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.

  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 ...