Introduction-ECO6416 - Introduction Modeling of a Data Set:...

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Introduction Modeling of a Data Set: Families of parametric distribution models are widely used to summarize a huge data set, to obtain predictions, assess goodness of fit, to estimate functions of the data not easily derived directly, or to render manageable random effects. The trustworthiness of the results obtained depends on the generality of the distribution family employed. Inductive Inference: This extension of our knowledge from a particular random sample to the population is called inductive inference. The main function of business statistics is the provision of techniques for making inductive inference and for measuring the degree of uncertainty of such inference. Uncertainty is measured in terms of probability statements, and that is the reason we need to learn the language of uncertainty and its measuring tool called probability. In contrast to the inductive inference, mathematics often uses deductive inference to prove theorems, while in empirical science, such as statistics, inductive inference is used to find new knowledge or to extend our knowledge. Probability, Chance, Likelihood, and Odds The concept of probability occupies an important place in the decision-making process under uncertainty, whether the problem is one faced in business, in
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This note was uploaded on 10/03/2011 for the course ECO 6416 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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Introduction-ECO6416 - Introduction Modeling of a Data Set:...

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