**Introduction:**

Probability plots if a graphing method for comparing two datasets. Probability plot help is important to understand the probability curves. We can compare either empirical set or any theoretical set or two theoretical sets. It means the following two plots.

I) P –P plot

II) Q- Q plot

**P – P plot:**

It mean Probability to Probability plot. It is a probability plot for assessing for two closed data’s. It will plot any two cumulative distribution functions.

**Q – Q plot:**

Here Q stands for Quartile. Q – Q plot mean Quartile to Quartile plot. It is used to plot any two probability distribution based on their quartiles of each other.

Here we will see an example for P – P probability plot help. Let us take any two cumulative distributions for the P-P probability help. Here F and G are the two cumulative distribution functions. Here the Probability plots F(x) and G(x) where x ranges from -∞ to +∞. Normally cumulative distribution has the range between (0, 1). Here the domain of the graph is between (-∞, +∞) and the unit square range is [0, 1] X [0, 1].

**Example**:

Let us consider an example for P – P plot. Here the two distributions do not overlap each other. Here F is below G then the P –P plot
will move from left to right along the bottom of the squares. Here x moves based on the support of the function F and it moves from 0 to
1.

Here we will understand the Q – Q plot help based on an example. Q-Q probability construction is based on the following steps,

- The main and the first step is calculating or estimating the plot will be drawn.
- The Q-Q probability will be based on the theoretical distribution with the final result we called as the cumulative function with the continuous probability. So the all quartile are uniquely obtained and plotted using the inverse of cumulative frequency with continuous data.