Data collection interpretation

Data collected for the finalist tollers should be audited and verified once more to ensure no misrepresentation has occurred. Often a more detailed analysis of financial data is undertaken. The guidelines shown in Table 2-1 are rules of thumb to use when interpreting a Dunn Bradstreet (D B) report. 

TIME SIGNAL DETECTION DATA COLLECTION IDENTIFICATION INTERPRETATION GOAL SELECTION CADET ANALYSIS... 

There is considerable overlap between the processes of data collechon and interpretation as discussed in earlier sections of this chapter. The nature of the data collected will be strongly influenced by the assumed relationship between the observable characteristics of errors and their underlying causes. Similarly, the interpretation process will also be driven by the causal model. 

Our research design, shown in Fig. 13.1, followed the typical action research cycle as proposed by Ferrance (2000) which involves the following five phases (1) Identification of problem area, (2) Collection and organisation of data, (3) Interpretation of data, (4) Action based on data and (5) Refiection and evaluation of results. Finally, the results are used in a new cycle of research. 

The most versatile data acquisition option is a stand alone data collection unit. At Glidden we use an Elexor Data Logger (S) for this purpose. It has its own microprocessor and BASIC Interpreter and communicates with the computer via the serial port. The unit can be configured with a wide variety of signal processing options. 

Additional examples of variability in data collection (which, in turn, affects data interpretation) include questionnaires and physical exam forms. Questionnaires often utilize open-ended questions that allow great variability in the type and extent of adverse event information gathered. Physical exam forms—even when designed in a checklist format—may elicit variable collection of adverse event data what is a serious event to one clinician may not be serious to another. 

Many sources of uncertainty must be taken into account in interpreting water quality data collected in the field. Probably the single program that has most prominently... 

Data collected in drift studies may later be interpreted in risk assessments in conjunction with toxicity data for specific sensitive areas. Eor example, a risk assessment for determination of appropriate mitigation (if necessary) may include field study data on exposure risk from drift, along with information on other routes of exposure (e.g., dislodgable residues, runoff, etc.) and toxicity data from laboratory and/or field study models. The results of such an assessment may be used to estimate whether a given exposure represents a hazard to any specific entity or ecosystem. 

Control field matrices are usually placed at the field site upwind and at a significant distance from the spray or re-entry area so as to avoid all obvious routes of contamination at the test site that may destroy the integrity of the control samples. However, the control matrices should not be placed so far away from the test site as to avoid any suspected contamination that might occur from drift or other sources of contamination. One may want to define better the conditions at the test site in order to interpret better the exposure data collected from the volunteers matrices. 

To construct the reference model, the interpretation system required routine process data collected over a period of several months. Cross-validation was applied to detect and remove outliers. Only data corresponding to normal process operations (that is, when top-grade product is made) were used in the model development. As stated earlier, the system ultimately involved two analysis approaches, both reduced-order models that capture dominant directions of variability in the data. A PLS analysis using two loadings explained about 60% of the variance in the measurements. A subsequent PCA analysis on the residuals showed that five principal components explain 90% of the residual variability. 

Detailed interpretation of kinetic test data collected for environmental purposes has allowed criteria for ground and surface water geochemical exploration to be selected. Parameters predicted from kinetic testing to be anomalous in both ground and surface waters were observed to occur reflecting the presence of both molybdenum mineralization and natural acid rock drainage. Kinetic testing is very expensive and careful use of the acquired... 

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