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As long as the cashier is honest, there is nothing wrong with this procedure! A dishonest cashier could, however, practice a procedure known as lapping Mr X left the hotel, and his account for $175 is one of the accounts receivable When he receives his statement at month s end, he sends in his check for $175 The cashier does not record the payment on Mr X s account Instead, the check is simply put in the cash drawer and the cashier removes $175 for personal use The cashier s remittance at the end of the shift will balance, but Mr X s account will still show an outstanding balance of $175 When Mr Y, who has an account in the city ledger for $285, sends in his payment, the cashier records $175 as a payment on Mr.

For our example, we changed all integer rounding (the default for integer variables), to hundredths rounding Running NORM, Step 4: Summarize Click on the Summarize tab, and click on Run (accepting the defaults) The results of this summary will be much more meaningful if you have included a nam le with the variable names or if you have explicitly named your variables in the Variables tab Otherwise, you have to know which variable is which This summary is an extremely valuable troubleshooting tool Look at the number and percent missing for each variable Do the numbers make sense, given what you know about the data set If any variable is missing for 100% of the cases, it may mean that you have made a coding error somewhere If it is not an error, the variable should be omitted from the analysis The matrix of missingness patterns is also very useful.

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If the number of patterns is small, this could be reported, as is, in your article where you would normally talk about the sample size If the number of patterns is large, it might be useful to present in table form only the patterns with the largest numbers of cases If there is a very large number of missingness patterns, it will be necessary to summarize the patterns, as we have done in this chapter Please note that the pattern representing complete data (if it exists) always appears at the top and that the pattern with the least data appears at the bottom It is not good if the pattern at the bottom shows all zeros (no data) If the number of cases with no data is large or puzzling, it could be due to a coding error somewhere.

This means that the ACK and NAK messages do not suffer from errors in their transmission In this way, every word found to have transmission errors is successfully corrected by means of one or more retransmissions In this case all the error-control capability is spent on error detection, so that dmin = l + 1, and the system is able to detect any error pattern of up to l errors The error probability is determined by the event of an undetected error pattern, that is, an error pattern with dmin = l + 1 or more errors:.

Whether or not it is an error, you should delete such cases before continuing Our rst example involved the 25 individual variables described above and in Table 42, as well as the 21 variables.

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