Abstract
Very often in statistics it is necessary to test hypotheses about the parameters of a population. A statistical hypothesis is an assumption made about some parameter. This assumption could be completely verified if the whole population could be examined. However, in most cases only estimates of the parameters obtained from random samples are available and the assumptions must be tested using these estimates. These tests are called tests of significance or tests of hypotheses.
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© 1968 Springer Science+Business Media New York
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Mulholland, H., Jones, C.R. (1968). Significance Testing And Confidence Intervals. In: Fundamentals of Statistics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-6507-3_9
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DOI: https://doi.org/10.1007/978-1-4899-6507-3_9
Publisher Name: Springer, Boston, MA
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