Stat 401B
Lab 2
1
Overview
In this lab you will look at residuals using JMP. The definition of a residual is the difference
between an observed value and a predicted value. The predicted value, and thus the residuals,
is determined by the type of problem you have (the statistical model).
Computer Exercises
The objective for these exercises is to show you how to get residuals using JMP.
1. We will go back to the abrasion data in the sample data files in JMP. Recall that this
file contains a sample of 40 abrasion (wear) values for parts from a production line.
There are two shifts represented.
2. One-sample problem. Model: Yi = µ + i
Residual = Yi − Y
(a) In order to create residuals for the one sample problem you need the value of the
sample mean. Use Analyze → Distribution to come up with the sample mean value
for the 40 abrasion measurements.
(b) Go to the data table and add a new column. To do this click on the red triangle
next to Columns. Select New Column. Name this column Residual.
(c) Highlight the Residual column in the data table and go to the Cols pull down
menu. Select Formula. A formula window will open. Enter the formula:
Abrasion − #
where # is the value of the sample mean you found in (a).
(d) Use Analyze → Distribution to analyze the residuals. You should have a histogram.
A box plot. A Normal Quantile Plot. Use Fit Distribution - Normal, to superimpose a normal curve on the histogram.
3. Two-sample problem. Model: Yij = µi + ij
Residual = Yij − Y i
(a) JMP will automatically calculate residuals for you from the Fit Y by X platform.
Go to Analyze → Fit Y by X and enter Abrasion as the Y, Response and Shift
as the X, Factor. Click on OK. Go to the red triangle pull down in the output
window and select Save - Save Centered. This will create a new column in your
data table labeled Abrasion centered by Shift. These are the residuals for the
two-sample problem.
(b) Use Analyze → Distribution to analyze the residuals, Abrasion centered by Shift.
You should have a histogram. A box plot. A Normal Quantile Plot. Use Fit
Distribution - Normal, to superimpose a normal curve on the histogram. Also
look at the equal standard deviation condition.
Note: Even though you have two samples of data, you end up with one
set of residuals.