Q-Q plot equivalent for discrete variable?

In summary, a Q-Q plot equivalent for discrete variable is a graphical method that compares the distribution of a discrete variable with a theoretical distribution. It differs from a regular Q-Q plot in that it uses step functions and is specifically designed for discrete variables. The purpose of this plot is to visually assess the fit between the observed data and the theoretical distribution. It is interpreted by comparing the plotted points to a diagonal reference line, and it is created by plotting quantiles of the data and theoretical distribution and connecting them with step functions.
  • #1
bradyj7
122
0
Hello,

You can use a Q-Q plot to visually test if 2 continuous variables are from the same distribution and you get a straight line.

Is there a way to visually test if 2 discrete variables are from the same distribution? Also is there a way to test it mathematically?

Thanks
 
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  • #2
You can do a Q-Q plot for discrete data, but it's a bit more tricky, i'll try to find a source for you.
 
  • #3
Thanks
 
  • #4
Hi there,

Apart from using a Q-Q plot is there any other way to test if two variables have the same distribution?

Thanks
 
  • #5
A chisquare test?
 

1. What is a Q-Q plot equivalent for discrete variable?

A Q-Q plot equivalent for discrete variable is a graphical method used to compare the distribution of a discrete variable with a theoretical distribution. It plots the quantiles of the observed data against the quantiles of the theoretical distribution, allowing for visual assessment of the match between the two.

2. How is a Q-Q plot equivalent for discrete variable different from a regular Q-Q plot?

A Q-Q plot equivalent for discrete variable is specifically designed for discrete variables, while a regular Q-Q plot is used for continuous variables. The main difference is that a Q-Q plot equivalent for discrete variable uses step functions instead of a continuous line to plot the quantiles.

3. What is the purpose of a Q-Q plot equivalent for discrete variable?

The purpose of a Q-Q plot equivalent for discrete variable is to visually assess whether a discrete variable follows a particular theoretical distribution. It can also be used to compare the distribution of two discrete variables or to identify potential outliers in the data.

4. How do you interpret a Q-Q plot equivalent for discrete variable?

A Q-Q plot equivalent for discrete variable is interpreted by comparing the plotted points to the diagonal reference line. If the points fall close to the line, it indicates a good fit between the observed data and the theoretical distribution. If the points deviate significantly from the line, it suggests a poor fit.

5. How do you create a Q-Q plot equivalent for discrete variable?

To create a Q-Q plot equivalent for discrete variable, you first need to calculate the quantiles of the observed data and the theoretical distribution. Then, plot the quantiles of the observed data on the x-axis and the quantiles of the theoretical distribution on the y-axis. Finally, connect the points with step functions to create the plot.

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