By Gerald Knight
Total this can be a solid booklet, however it will be a lot nicer in the event that they supplied Excel worksheets with the knowledge utilized in the book's examples. a few pattern code is equipped for dowload on Oreilly's web site, yet this doesn't comprise instance information. still, the ebook is worthy .
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Additional resources for Analyzing Business Data with Excel
The top ten is the default, but I can select any number of items to show using the options on the right side of the dialog. In Figure 2-6 the last city is named (blank). This could be useful if we had some blank city names in the data. But we don't. To remove the blank entry, I click on the arrow in cell A4 of Figure 2-6. This displays the dialog in Figure 2-8. Figure 2-5. Changing from Count to Average This allows me to control which offices will appear on the table. Here, I have unchecked (blank) to exclude it.
6 days on average while St. Paul takes over 42 days. Some of the difference might be understandable if there is a difference in the kinds or value of orders between the offices. 3. Multiple Data Items Next we check to see if the average order amount is related to average order age. First, I drag Order Amount from the field list into the data area. This adds Count of Order Amount as a second data item. To change to the average, I right-click on one of the cells containing data for Count of Order Amount.
Some error is expectedsome difference between the forecast and the actual value. In most cases, then, it is not enough to make a forecast. We also need to know how accurate the forecast will be. This means that the prediction is not an exact value but a range with a known probability. This chapter looks at predicting the workload for a typical business process. The example forecasts the volume of calls coming into a call center, but the techniques can be applied to many other problems. This type of forecasting uses only the past values of the item being predicted.
Analyzing Business Data with Excel by Gerald Knight