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### Evaluation of Data

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Abstract

Data are facts or figures from which conclusions can be inferred. The word carries with it connotations of objectivity, freedom from bias and personal prejudice, and an analytical approach in which precise measurement systems are applied to obtain information which in turn will be subjected to further analysis and interpretation leading to conclusions about the thing, group, or class of things to which the measurement system was applied. The long step between collection of information and conclusions is, to a large extent, evaluation of data. Furthermore, many of the considerations that should be applied to the proper evaluation of data should also be applied to the preceding steps in the operation. That is, planning the collection of data and the data collection itself. Data evaluation can be simple, and it can be extremely complex. An examination of a simple problem and one of greater complexity will serve to illustrate several of the fundamental concepts. In the simple case, suppose we have two blocks of concrete and the question is to decide which of the two is heavier. We also have available a scale of sufficient capacity that will weigh these blocks to the nearest pound. Accuracy and precision of the measurement system are not in question. We put Block A on the scale, and it weighs 83 lb; we put Block B on the scale, and it weighs 112 lb. These are the data. Evaluation of these data is to look at the two numbers and decide whether one is larger than the other. The analysis shows that the weight of Block B (112 lb) exceeds the weight of Block A (83 lb), and, therefore, we conclude that Block B is heavier than Block A. We know all there is to know, all that needs to be known in order to answer the original question with complete confidence. We do not have to say that probably Block B is heavier than Block A, or there are indications that Block B is heavier than Block A, or the trend of the data seems to indicate that it is likely that Block B is heavier than Block A. Block B is heavier than Block A and that's that.

Author Information:

McLaughlin, J. F.
Professor of civil engineering, Purdue University, Lafayette, Ind.

Hanna, S. J.
Instructor in civil engineering, Purdue University, Lafayette, Ind.

Committee/Subcommittee: C09.60

DOI: 10.1520/STP49864S