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(Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics) For a project, we may need to prepare multiple versions. Different statistical methods or models may require different input formats of data. Data Preparation for Different Analysis Purposes For a project dealing with a particular scientific question or with different objectives, different statistical methods and predictive models may need to be used.Recall from the field statistics that the 2007 year had approximately 6 months' worth of transactions, while 2011 had only the first 10 months of transactions. This is in contrast to debit card payments that remained consistent. For instance, cash payments dropped significantly in 20 before increasing again in 2011. This provides an understanding of how payments fluctuate from year to year. The amounts areįIGURE 3.13 Results of the Stratification for Cash PaymentsįIGURE 3.14 Creating a Pivot Table View and ResultsĬross-tabulated both by rows and columns.
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In this example, we display by row the tender payment type and by column the year. It allows for a better overall picture to analyze data. Pivot Table allows data to be displayed, organized, and summarized in different views (Figure 3.14). The year field was previously added, so now we can perform additional data profiling using the year field. It is also interesting to note that neither the percentage of number of records nor the percentage of the payment amounts follows the same pattern as the debit card payments.įIGURE 3.9 Summarization of Payment Tender TypesįIGURE 3.10 Summarization of Tender Type ResultsįIGURE 3.11 Stratification of Payment Amounts by Tender TypesįIGURE 3.12 Results of the Stratification for Debit Card Payments The stratification of cash payments shows one negative amount in Figure 3.13. Similarly, there are no negatives for Visa, MasterCard, and AME (not shown). There are no negative amounts for debit card transactions as seen in Figure 3.12. Stratifying the debit card payments shows that 9 7 percent of the transactions and 90 percent of the total dollar values are $50 dollars and below. We determined that there were only these six tender or payment types when we summarized the data. In this case, we selected the tender payment field to group so that cash, debit, MasterCard, Visa, and so on amounts will be displayed The ranges can be at a fixed increment or, better yet, you can set the explicit ranges to produce results that are more meaningful to the context of the data. Now that you are aware that the average payment is $19.48, you can stratify the amounts to give you a range of how many transactions occurred in each range as displayed in Figure 3.11. Visa, MasterCard, and American Express (AME) are accepted but are not as popular with their customers. We can see in Figure 3.10, that debit cards are used most frequently, followed by cash payments. The tender or payment type can be summarized to identify the number of transactions for each category and total the amounts as shown in Figure 3.9. If you were to apply sampling techniques, you would want to pull more samples from after the noon hour. or at noon, depending on the day of the week.
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This makes perfect sense, since the business opens either at 11:00 a.m. The most payments are processed after the noon hour, with 80,609 or 95 percent of transactions taking place. The payment time also provides valuable information in Figure 3.8. The monthly and daily number of transactions are also displayed in field statistics, as shown in Figure 3.7. Most frequent payments and sales occur on Fridays and September was the best month for the client. Therefore, theįIGURE 3.6 Isolating the Field Statistics of the Payment Amount The most frequent or common day of the week is Friday and the most common month is September. The statistics for the date field shows the date of the earliest and latest record so you know the date range for the data you will be analyzing. A discussion of the sample and population standard deviation values follows in Chapter 4. Both the minimum value and maximum value amount should be examined in detail. Note that the average payment for the sales is $19.48. By putting your cursor over items it turns into a hand icon, and those items can be clicked on to drill down to detail levels and display the records pertaining to those items. The net value is the total of the field or column, which equals the control total. The only numeric field that is of use is the pay amount field, which we will look at closer in Figure 3.6.įIGURE 3.5 Field Statistics of the Payment Tender File Numeric, date, and time fields are displayed in field statistics in Figure 3.5. FIGURE 3.4 Payment Tender Type File Example in IDEA