The Cumulative Distribution Plots menu item gives you access to two plots designed to show you a variable's cumulative distribution. These plots are:

  THE QUANTILE PLOT
  THE NORMAL PROBABILITY PLOT

The Quantile plot (Q-Plot) pictures a variable's cumulative distribution by plotting the value of a specific datum versus the fraction of the data that is smaller than the specific datum. The jagged line represents the variable's cumulative distribution.

The Normal Probability Plot (NP-Plot) pictures a variable's cumulative distribution by plotting the value of a specific datum versus the Z-score that would be obtained for the datum under the assumption of normality. 

Note that the NP-Plot is the same as the the Q-Plot except that the Q-plot's Fraction of Data (empirical probability) is converted into the NP-Plot's Z-Scores, where the Z-Scores has the stated probability.

ABOUT THE Q-PLOT
The Q-Plot is used to help decide on the symmetry of a variable's distribution. Symmetry is not displayed in the usual sense. Rather, for a symmetric distribution, the points in the upper half of the plot will stretch out toward the upper right the same way the points in the bottom half stretch out toward the lower left.

There are several reasons why symmetry is important for data analysis: 1) The center of a distribution is unambiguous for a symmetric distribution. 2) Symmetric distributions are easier to understand (the upper part is like the lower part); and 3) Symmetric distributions are amenable to stronger statistical analysis than asymmetric distributions.

When you click on the Y button at the top of the graph you will be presented with a list of variables to display. Clicking on a variable will change the plot to display that variable on the Y-axis. (If there are only two varibles, it toggles between them.)

Clicking on the X button at the top of the graph toggles the X-axis between "Fraction of Data", and "Z-Score of Fraction of Data". It also toggles the entire graph between a Quantile Plot and a Normal Probability Plot. 

ABOUT THE NP-PLOT
In the NP-Plot, the jagged line represents the variable's distribution and the straight line represents a normal distribution. If the jagged line is roughly linear, so that it approximately follows the straight line, the variable has an approximately normal distribution.

Systematic departures from a straight line indicate non-normality. Such departures include large deviations, which indicate outliers; asymmetric departures at one end or the other, indicating skewness; and horizontal segments, plateaus or gaps, which indicate discrete data.

Normality is important because very many inferential statistical procedures assume that the data are normally distributed. The normal-probability plot gives us a visual approach to checking on this critical assumption.

When you click on the Y button at the top of the graph you will be presented with a list of variables to display. Clicking on a variable will change the plot to display that variable on the Y-axis. (If there are only two varibles, it toggles between them.)

Clicking on the X button at the top of the graph toggles the X-axis between "Fraction of Data", and "Z-Score of Fraction of Data". It also toggles the entire graph between a Quantile Plot and a Normal Probability Plot. 
