Nonparametric two sample tests for scale and their applications in quality control - V, Bhatt Mayank
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One of the important branches of modern statistics is statistical inference. It is concerned with two types of problems: estimation and tests of hypotheses. The classical approach of the statistical inference is the parametric inference. The title of the tests "parametric" suggests the central importance of the population, or its parameter, in their use and interpretation. The ¿¿¿¿ and ¿¿¿¿ tests are the most familiar and widely used parametric tests, and the Pearson product-moment correlation coefficient and its associated significance test are the most familiar parametric approaches to…mehr

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Produktbeschreibung
One of the important branches of modern statistics is statistical inference. It is concerned with two types of problems: estimation and tests of hypotheses. The classical approach of the statistical inference is the parametric inference. The title of the tests "parametric" suggests the central importance of the population, or its parameter, in their use and interpretation. The ¿¿¿¿ and ¿¿¿¿ tests are the most familiar and widely used parametric tests, and the Pearson product-moment correlation coefficient and its associated significance test are the most familiar parametric approaches to assessing association. Sometimes the researcher is able to determine whether the conditions of a particular statistical model are met in his research, but more often he simply has to assume that they are met thus the conditions of a statistical model of a test are often called the "assumptions" of the test. The parametric inference is entirely depending upon the following assumptions.