Test for Normality-ECOC6416

Test for Normality-ECOC6416 - sample was drawn from...

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Test for Normality The standard test for normality is the Lilliefors' statistic. A histogram and normal probability plot will also help you distinguish between a systematic departure from normality when it shows up as a curve. Lilliefors' Test for Normality: This test is a special case of the Kolmogorov-Smirnov goodness- of-fit test , developed for testing the normality of population's distribution. When applying the Lilliefors test, a comparison is made between the standard normal cumulative distribution function , and a sample cumulative distribution function with standardized random variable . If there is a close agreement between the two cumulative distributions, the hypothesis that the
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Unformatted text preview: sample was drawn from population with a normal distribution function is supported. If, however, there is a discrepancy between the two cumulative distribution functions too great to be attributed to chance alone, then the hypothesis is rejected. The difference between the two cumulative distribution functions is measured by the statistic D, which is the greatest vertical distance between the two functions. You might like to use the well-known Lilliefors' Test for Normality to assess the goodness-of-fit....
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This note was uploaded on 10/04/2011 for the course ECO 6416 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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