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Cohort analysis is a kind of behavioral analytics that breaks the data in a data set into related groups before analysis. These groups, or cohorts , usually share common characteristics or experiences within a defined time-span.
Automatic aggregation of raw event data into relevant data sets for rapid access, filtering and analysis; Ability to query data in an unlimited number of ways, enabling users to ask any business question; Extensive library of built-in analysis functions such as cohort, path and funnel analysis; A visualization component
Path analysis provides a visual portrayal of every event a user or cohort performs as part of a path during a set period of time. While it is possible to track a user's path through the site, and even show that path as a visual representation, the real question is how to gain these actionable insights.
Case–control study versus cohort on a timeline. "OR" stands for "odds ratio" and "RR" stands for "relative risk".In statistics, epidemiology, marketing and demography, a cohort is a group of subjects who share a defining characteristic (typically subjects who experienced a common event in a selected time period, such as birth or graduation).
Visual analytics seeks to marry techniques from information visualization with techniques from computational transformation and analysis of data. Information visualization forms part of the direct interface between user and machine, amplifying human cognitive capabilities in six basic ways: [2] [5]
Cohort (taxonomy), in biology, one of the taxonomic ranks; Cohort study, a form of longitudinal study used in medicine and social science; Cohort analysis, a subset of behavioral analytics that takes the data from a given data set; Generational cohort, an aggregation of individuals who experience the same event within the same time interval
In "Visualization Analysis and Design" Tamara Munzner writes "Computer-based visualization systems provide visual representations of datasets designed to help people carry out tasks more effectively." Munzner agues that visualization "is suitable when there is a need to augment human capabilities rather than replace people with computational ...
Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots , histograms , probability plots , spaghetti plots , residual plots, box plots , block plots and biplots .