Examples of analytical thinking

Analytical Rubric for Contour Maps (earth science) Neatness Map is crystal clear, no isolines touch or cross, no stray pen or pencil marks and overall appearance shows care and attention to detail. Numbers are legible, yet unobtrusive, symbols are unmistakable. 3 points Map is clear, although signs of carelessness may appear. Isolines do not cross, and stray pencil marks are minimal or mostly erased. Numbers are legible, symbols conform with handout guidelines. 2 points Map lacks clarity. Isolines are nebulous, extraneous marks litter the page. Numbers are messy, symbols confusing. 1 point Map is an utter mess. No attempt at neatness is evident. Includes a blank page. 0 points Completeness Every isoline is present on map, and clearly labeled. Proper lines are used for topographic elements, and symbols represent all known or discernible structures. 3 points Requires isolines are present, some labels may be missing. Most identifiable structures in landscape are represented by appropriate symbols. 2 points Some isolines missing, labels intermittent. Few structures are represented by the appropriate symbols. 1 point More isolines are missing than are present, labels rare to nonexistent. Symbols for other structures are not present whatsoever. 0 points Accuracy Map clearly corresponds to given landscape. Geologic formations are clearly identifiable, and distances between objects on map are directly related to reality. 3 points Map represents landscape. General contours are identifiable, although details may be slightly off. Distances are mostly consistent with reality. 2 points Map is a gross interpretation of reality. Hills and valleys exist, but shapes vary from given landscape. Distances between objects are only roughly proportional to given landscape. 1 point Are you sure you were mapping the landscape I gave you? 0 points by Joel Stachura, 1995

Frequently, a specific method is used for only a few sample analyses. The question should be raised as to whether this method also needs to be validated using the same criteria as recommended for routine analysis. In this case, the validation may take much more time than the sample analysis and may be considered inefficient, because the cost per sample will increase significantly. The answer is quite simple: Any analysis is worthwhile only if the data are sufficiently accurate; otherwise, sample analysis is pointless. The suitability of an analysis method for its intended use is a prerequisite to obtaining accurate data; therefore, only validated methods should be used to acquire meaningful data. However, depending on the situation, the validation efforts can be reduced for non-routine methods. The CITAG/ EURACHEM guide (19) includes a chapter on how to treat non-routine methods. The recommendation is to reduce the validation cost by using generic methods, for example, methods that are broadly applicable. A generic method could, for example, be based on capillary gas chromatography or on reversed phase gradient HPLC. With little or no modification, the method can be applied to a large number of samples. The performance parameters should have been validated on typical samples characterized by sample matrix, compound types and concentration range.

Examples of analytical thinking

examples of analytical thinking


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