By Robert P. Trueblood, John N. Lovett Jr. (auth.)
This booklet is not only one other theoretical textual content approximately data or info mining. No, as an alternative it truly is aimed for database directors who are looking to use SQL or bolster their realizing of information to help facts mining and purchaser courting administration analytics.
Each bankruptcy is self-contained, with examples adapted to genuine enterprise purposes. and every research procedure might be expressed in a mathematical layout for coding as both a database question or a visible uncomplicated strategy utilizing SQL. bankruptcy contents contain formulation, graphs, charts, tables, facts mining innovations, and more!
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Extra resources for Data Mining and Statistical Analysis Using SQL
There was an old World War II ordnance site in California used for training and maneuvers. Much of the ordnance fired for practice and training of the troops was still buried throughout the site, so the task included assessing the extent of this ordnance (some of which was still live) by field sampling and investigation. Our involvement was to take the field data and determine whether or not we could verify historical target and impact areas from the sampled finds. We developed a statistical model to calculate the ordnance densities in the sampled areas, find the point in the field about which the ordnance finds clustered, then determine the standard deviation of distances of these ordnance locations from the central point.
Jl • 1M ~ 1\ \ . ,_. io... • J v J / . . 7 140 160 180 200 Miles Figure 2-6. '' The other owner says this sounds reasonable, but the split rate is too complicated. Why wouldn't the original flat rate idea apply? 26% of the customers are expected to be within the small circle and would pay the $20 rate. 44%) would pay the $50 rate. 32 The owners decide to round this to a $25 flat rate. For any customers who might call for pick-up outside the 94-mile "largest" circle, a surcharge is added. Wasn't that fun?
Number ofLimousine Pick-Up Points Falling Within Each Mileage Interval from the Dispatching Location at the Airport HISTOGRAM INTERVAL (MILES) 48 OBSERVED FREQUENCY (0) [0 -7) 5 [7- 14) 7 [14- 21) 8 [21 - 28) 11 [28- 35) 13 [35- 42) 15 [42- 49) 14 [49- 56) 11 [56- 63) 7 [63 -70) 5 [70 -77) 2 [77- 84) 2 Goodness ofFit SQL/Query The data shown in Table 3-1 can be generated by executing a set of SQL queries. In our first query we create an initial version of Table 3-1 by forming the intervals of width 7 and by giving each interval an identification number.
Data Mining and Statistical Analysis Using SQL by Robert P. Trueblood, John N. Lovett Jr. (auth.)