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Normal probability plot

Page history last edited by Trever Wilson 9 years, 3 months ago

The normal probability plot (also known as a QQ plot) is a specialized graph that helps you to decide whether using a normal model is appropriate. If the distribution of your data is normal, the data plots will go in an approximate diagonal line with no deviations. A normal probability plot compares each data value with what would be the data value's z-score if it were perfectly normal. A normal probability plot is placed on the x (Expected Normal Value) and y axis with plots lined in their appropriate position. The "perfect plot" will be shown with a diagonal line. 

 

For Example: Data percentages were collected from various countries on the amounts of Cannabis. As you can see in the Q-Q Plot below, the data values keep in an approximate diagonal line, so you can continue with a Normal model. 

 

How to Generate a Normal Probability Plot  Using SPSS 

  • In the menu bar, click Analyze.
  • Highlight "Descriptive Statistics" with your mouse and a side menu should appear.
  • In the side menu, open the Q-Q plot option. 
  • On the left of the new window, you will find your quantitative variable you are wanting to test. Drag that variable to the "Variables" area.
  • Click OK.
  • In the Output window of your SPSS, your graph should appear. You need to scroll through your output data until you find the plot titled: "Normal Q-Q Plot of (Name of Data)". 

 

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