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By R. Lyman Ott, Micheal T. Longnecker

Information is a idea method. during this finished advent to statistical equipment and knowledge research, the method is gifted using a four-step procedure: 1) amassing facts, 2) summarizing information, three) studying info, and four) speaking the result of information analyses.

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They list many of the potential sources of errors commonly found in surveys with guidelines on how to avoid these pitfalls. A discussion of some of the issues raised in these brochures follows. Problems Associated with Surveys survey nonresponse Even when the sample is selected properly, there may be uncertainty about whether the survey represents the population from which the sample was selected. Two of the major sources of uncertainty are nonresponse, which occurs when a portion of the individuals sampled cannot or will not participate in the survey, and measurement problems, which occur when the respondent’s answers to questions do not provide the type of data that the survey was designed to obtain.

For example, in an experiment evaluating the effectiveness of several drugs for reducing blood pressure, the age or physical condition of the participants in the study may decrease the effectiveness of the drug. 3 Scientific Studies 29 account. Also, the environmental conditions encountered during the experiment may reduce the effectiveness of the treatment. In our example, we would want to avoid having the comparison of the tire brands distorted by the differences in the four cars. The experimental design used to accomplish this goal is called a randomized block design because we want to ‘‘block’’ out any differences in the four cars to obtain a precise comparison of the four brands of tires.

The nitrogen levels are 40, 50, and 60 pounds per plot and the phosphorus levels are 10, 20, and 30 pounds per plot. 7 are assigned at random to the experimental units (the plots of land planted with corn). It is not necessary to have the same number of levels of both factors. 7 Factor–level combinations for the 3 ϫ 3 factorial experiment Treatment Phosphorus Nitrogen 1 10 40 2 10 50 3 10 60 4 20 40 5 20 50 6 20 60 7 30 40 8 30 50 33 9 30 60 example, we could run an experiment with two levels of phosphorus and three levels of nitrogen, a 2 ϫ 3 factorial experiment.

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