Microsoft Office Tutorials and References
In Depth Information
Table 3.3 Modified quarterly data for product E
Qtr 1
Qtr 2
Qtr 3
Qtr 4
Yearly Total
Yr1
23
14
56
78
171
Yr2
27
20
67
89
203
Yr3
34
30
73
83
220
Yr4
43
32
85
98
258
Yr5
50
36
101
123
310
Yr6
63
46
125
146
380
sales in thousands of dollars
Now let us proceed with the analysis. First, we will apply the Histogram tool to
explore the quarterly data behavior in greater depth. There is no guarantee that the
tool will provide insight that is useful, but that’s the challenge of data analysis—it
can be as much an art as a science. In fact, we will find the Histogram tool will be
of little use. Why? It is because the tool does not distinguish between the various
quarters. As far as the Histogram tool is concerned, a data point is a data point,
without regard to its related quarter; thus we see the importance of the context of
data points. Had the data points for each quarter been clustered in distinct value
groups (e.g. all quarter 3 values clustered together) the tool would have been much
more useful. See Exhibit 3.19 for the results of the histogram with bin values in
increments of 10 units starting at a low value of 5 and a high of 155. There are
Exhibit 3.19 Histogram results for all product E adjusted data
 
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