Vol. 4, No. 3
from Dr. Cleary
A scatter diagram will indicate whether two variables'in
this case, temperature and defects'are related to each other, or whether
there is a correlation between the two. If one of the variables appears to
have an effect on the other, then regression analysis will be appropriate.
Since May Aculpa wants to establish whether there is indeed a correlation, an
individual moving range chart will not be of any help here. (See Practical
Tools for Continuous Improvement (Volume I, Statistical Tools), Jacqueline
D. Graham, Ph.D., and Michael J. Cleary, Ph.D., pp. 298-311).
The same data can be charted using CHARTrunner from PQ Systems as follows:
Since May Aculpa assumes that temperature affects the number of defects (rather than the other way around), temperature becomes the independent variable, represented on the horizontal axis. The number of defects becomes the dependent variable, on the vertical axis. The line of best fit shows the relationship:
Y = 13.4 = 1.66x
This means that as the temperature goes up, so does the number of defects. A correlation coefficient of .93 suggests a rather strong relationship between the two variables.
Copyright 2002 PQ Systems.
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