Describing categorized data

In this chapter we will start to look at data where no measurements are made on individuals. Instead, each individual is placed in a category and the numbers in each category are then counted. A classic example is where we look at a medical treatment and declare each patient s outcome as successful or unsuccessful . We then count the number of successes and failures. This type of data was introduced in Chapter 1 as nominal scale data. 

Essential Statistics for the Pharmaceutical Sciences Philip Rowe 

We have already met P values in the context of significance testing and it is singularly unfortunate that the same letter should be introduced for a second important function, but then that is statistics for you. (To achieve some clarity. I will use lower case p for proportion and upper case P in hypothesis testing.) 

2 What determines the precision of sample estimates of a proportion  

The precision with which a proportion within the population can be estimated from a sample depends solely on the number counted. Greater numbers - greater precision. 

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All of the tests described for acute diarrhea would be used to establish a diagnosis of chronic diarrhea because the differential diagnosis is more complicated. The data obtained can help categorize the diarrhea as watery, inflammatory, or fatty, narrowing the focus on a primary disorder. 

In Section 1.1, parametric methods for improving tlie quality of correlated electronic-structure calculations were discussed in detail. Similarly, in Section 8.4.3, the mild parameterization of density functional methods to give maximal accuracy was described. Given that background, and the substantial data presented in diose earlier chapters, this section will only recapitulate in a rough categorical fashion tlie various approaches whose development was motivated by a desire to compute more accurate thermochemical quantities. 

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