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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]
Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...
Statistics (from German: Statistik, orig. "description of a state, a country" [1]) is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [2]
data data analysis data set A sample and the associated data points. data point A typed measurement — it can be a Boolean value, a real number, a vector (in which case it is also called a data vector), etc. decision rule decision theory degrees of freedom density estimation dependence dependent variable descriptive statistics design of ...
Plots play an important role in statistics and data analysis. The procedures here can broadly be split into two parts: quantitative and graphical. Quantitative techniques are a set of statistical procedures that yield numeric or tabular output. Examples of quantitative techniques include: [1] hypothesis testing; analysis of variance
The use of descriptive and summary statistics has an extensive history and, indeed, the simple tabulation of populations and of economic data was the first way the topic of statistics appeared. More recently, a collection of summarisation techniques has been formulated under the heading of exploratory data analysis : an example of such a ...
In statistics, compositional data are quantitative descriptions of the parts of some whole, conveying relative information. Mathematically, compositional data is represented by points on a simplex. Measurements involving probabilities, proportions, percentages, and ppm can all be thought of as compositional data.
The dot plot as a representation of a distribution consists of group of data points plotted on a simple scale. Dot plots are used for continuous, quantitative, univariate data. Data points may be labelled if there are few of them. Dot plots are one of the simplest statistical plots, and are suitable for small to moderate sized data sets.