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Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...
Graphical statistical methods have four objectives: [2] The exploration of the content of a data set; The use to find structure in data; Checking assumptions in statistical models; Communicate the results of an analysis. If one is not using statistical graphics, then one is forfeiting insight into one or more aspects of the underlying structure ...
Orange – A visual programming tool featuring interactive data visualization and methods for statistical data analysis, data mining, and machine learning. Pandas – Python library for data analysis. PAW – FORTRAN/C data analysis framework developed at CERN. R – A programming language and software environment for statistical computing and ...
Data representations and transformations that convert all types of conflicting and dynamic data in ways that support visualization and analysis; Techniques to support production, presentation, and dissemination of the results of an analysis to communicate information in the appropriate context to a variety of audiences.
Data are analyzed using techniques such as calculation, reasoning, discussion, presentation, visualization, or other forms of post-analysis. Prior to analysis, raw data (or unprocessed data) is typically cleaned: Outliers are removed, and obvious instrument or data entry errors are corrected.
Exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.
Data visualizations are often used in infographics and may make up the entire infographic. There are many types of visualizations that can be used to represent the same set of data. Therefore, it is crucial to identify the appropriate visualization for the data set and infographic by taking into consideration graphical features such as position ...
Data processing is the collection and manipulation of digital data to produce ... interpretation and presentation of data." ... using manual processing methods.
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