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Follow these steps to add box plots for each level of **DRUG**
to the **Fit(Y X)** window.

Select an area for the box plot. |

Drag the cursor until you have a rectangle of suitable size.

Choose Analyze:Box Plot/Mosaic Plot ( Y ). |

Select CHANG_BP in the list at the left, then click the Y button. |

This assigns the **Y** role to this variable.

Select DRUG in the list at the left, then click the X button. |

This assigns the **X** role to this variable and
requests a separate box plot for each level of **DRUG**.
Your variables dialog should now appear,
as shown in Figure 15.10.

Click the Output button. |

The output options dialog shown in
Figure 15.11 appears on your display.
In this dialog, you can specify options to determine
the output produced by the box plot.

Click on Means. |

**Means** displays mean diamonds for all boxes.
The central line in the mean diamond marks the mean;
the size of the mean diamond is two standard deviations,
one above and one below the mean.

Click OK in both dialogs to create the Box Plots. |

Examine the box plot representing the four levels of **DRUG**.
Recall that the central line in each mean diamond marks
the mean while the height of the mean diamond shows one
standard deviation on either side of the mean.
The box and whiskers display percentiles for the data.
(See Chapter 4, "Exploring Data in One Dimension," for a complete description
of the parts of the box plot.)

Follow these steps to hide the display of box and whiskers in order to display the means and standard deviations better.

Click on Observations in the box plot pop-up menu. |

This toggles the display of observations and thus
turns off the display of the box, whiskers,
and individual observations in the box plot.

**Figure 15.13:** Box Plot Pop-up Menu

Click on Values in the box plot pop-up menu. |

This toggles the display of values of the mean for each box plot.

The largest effect noted in these plots is that
drugs **1** and **2** have a higher average increase
in systolic blood pressure than drugs **3** and **4**
(averaged over all three levels of **DISEASE**).
This difference resulted in the significant main effect
for **DRUG** that was observed in the **Type III Tests** table.

Repeat the preceding steps and display box plots for the levels of DISEASE. |

The differences between the three **DISEASE** levels
are not as pronounced as those observed for **DRUG**.
Disease **3** is associated with a lower average increase
in systolic blood pressure than the other two diseases
(averaged over all four levels of **DRUG**).
The smaller *p*-value observed for the **DRUG** main
effect is more evidence that the mean differences for
**DISEASE** are not as pronounced as those for **DRUG**.
This example illustrates one way to use
**Analyze:Fit** to fit the general linear model.
Turn to the next chapter to see how
to fit the generalized linear model.

Related Reading | Box Plots, Chapter 33. |

Related Reading | Linear Models, Chapter 39. |

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