None of the above tests show the dependency of categorical variables. Chi-Square test is the best statistical weapon for doing the job. The main idea behind the test is the following clause [2]— “Goodness of fit.” Let’s make it a little bit easier with an example. Suppose you t...
Acontingency tableis a tabulation or count of two categorical variables. In the case of the McNemar’s test, we are interested in binary variables correct/incorrect or yes/no for a control and a treatment or two cases. This is called a 2×2 contingency table. ...
A common way to learn about a system’s properties is to analyze temporal fluctuations in associated variables. However, conclusions based on fluctuations from a single entity can be misleading when used without proper reference to other comparable entities or when examined only on one timescale. ...
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The following instructions have been tested with Python 3.6.8 on Ubuntu (16.04.5 LTS). Install in editable mode First, define the variables for the paths we will use: GIT=/path/to/where/you/put/repos ENVS=/path/to/where/you/put/virtualenvs ...
Correlation ratio (for categorical-numerical) Squares represent categorical-featured-related variables and circles represent numerical-numerical correlations. Note that the trivial diagonal is left empty, for clarity. IMPORTANT: categorical-categorical associations (provided by the SQUARES showing the uncertai...
Squares represent categorical-featured-related variables and circles represent numerical-numerical correlations. Note that the trivial diagonal is left empty, for clarity. IMPORTANT: categorical-categorical associations (provided by the SQUARES showing the uncertainty coefficient) are ASSYMMETRICAL, meaning tha...
Shaked Zychlinski: The Search for Categorical Correlation is a great article about different types of variable interactions that was the basis of that analysis in Sweetviz. Drazen Zaric: Better Heatmaps and Correlation Matrix Plots in Python was the basis for our association graphs. And of course...
The following instructions have been tested with Python 3.6.8 on Ubuntu (16.04.5 LTS). Install in editable mode First, define the variables for the paths we will use: GIT=/path/to/where/you/put/repos ENVS=/path/to/where/you/put/virtualenvs ...