Design of Experiments

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To use statistical methods to make decisions, we need access to data. Consider the following examples about decision making. 1. A government agency wants to find the average income of households in the United States. 2. A company wants to find the percentage of defective items produced on a machine. 3. A researcher wants to know if there is an association between eating unhealthy food and cholesterol level. 4. A pharmaceutical company has developed a new medicine for a disease and it wants to check if this medicine cures the disease. All of these cases relate to decision making. We cannot reach a conclusion in these examples unless we have access to data. Data can be obtained from observational studies, experiments, or surveys. This article is devoted mainly to controlled experiments. However, it also explains observational studies and how they differ from surveys.

Suppose two diets, Diet 1 and Diet 2, are being promoted by two different companies and each of these companies claims that its diet is successful in reducing weight. A research nutritionist wants to compare these diets with regard to their effectiveness for losing weight. Following are the two alternatives for the researcher to conduct this research. 1. The researcher contacts the persons who are using these diets and collects information on their weight loss. The researcher may contact as many persons as she has the time and financial resources for. Based on this information, the researcher makes a decision about the comparative effectiveness of these diets. 2. The researcher selects a sample of persons who want to lose weight, divides them randomly into two groups, and assigns each group to one of the two diets. Then she compares these two groups with regard to the effectiveness of these diets. The first alternative is an example of an observational study, and the second is an example of a controlled experiment.

When the experimenter controls the (random) assignment of elements to different...
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