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Table 6.11 ANOVA single factor analysis for missing reefers
explicitly controlling the collection of observed data is Experimental Design .
Experimental design permits researchers to refine their understanding of how factors
affect the dependent variables in a study. Through the control of factors and their
levels, the experimenter attempts to eliminate ambiguity and confusion related to
the observed outcomes. This is equivalent to eliminating alternative explanations of
observed results. Of course, completely eliminating alternative explanations is not
possible, but attempting to control for alternative explanations is the hallmark of a
well conceived study: a good experimental design.
There are some studies where we do not actively become involved in the manip-
ulation of factors. These studies are referred to as observational studies .Our
refrigerated container example above is best described as an observational study,
since we have made no effort to manipulate the study’s single factor of concern—
Port. These ports simply happen to be where the shipping firm has terminals. If
the shipping firm had many terminal locations and it had explicitly selected certain
ports to study for some underlying reason, then our study would have been best
described as an experiment . In experiments we have greater ability to influence
factors . There are many types of experimental designs, some simple and some quite
complex. Each design serves a different purpose in permitting the investigator to
come to a scientifically focused and justifiable conclusion. We will discuss a small
number of designs that are commonly used in analyses. It is impossible to exhaus-
tively cover this topic in a small segment of a single chapter, but there are many
good texts available on the subject if you should want to pursue the topic in greater
detail.
 
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