---
title: "The relationship between cdf and density plots"
canonical: "https://modelassist.epixanalytics.com/space/EA/26575477/The%20relationship%20between%20cdf%20and%20density%20plots"
format: markdown
---
[For a continuous variable the gradient (or slope) of a cdf plot](https://epixanalytics.atlassian.net/wiki/spaces/EA/pages/26575476/) is equal to the probability density at that value. That means that the steeper the slope of a cdf the higher a density or histogram plot would look at that point:

  


![image](media://7c8d262a-49bf-4d72-8fde-9354726d9966)

  


The disadvantage of a cdf is that one cannot readily determine the central location or shape of the distribution. We cannot easily recognize common distributions like a triangular, normal, and uniform. Looking at the plots below, you will readily identify the distribution form from the left panels, but not so easily from the right panels:

  


![image](media://b2fd4b9f-144b-4e5e-bafe-243396cfecd5)

  


  


For a discrete distribution, the cdf increases in steps equal to the probability of the x-value occurring:

  


![image](media://a2b1e966-2ccb-4607-afe2-de64adc81baf)

  


  


  


  


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