Chi-squared Test - Goodness of Fit Test

# Chi-squared Test - Goodness of Fit Test - Section 15.2...

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1 Section 15.2 Chi-squared Test for Goodness of Fit

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2 Test for Goodness of Fit • So far, we have assumed the probability distribution for a particular set of data is known. • What if we don’t know the distribution? • What if we aren’t sure our assumption is correct?
3 For the Normal and Weibull distributions, we could do probability plots to see if the data fit the distribution.

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4 We can use also use the Chi-Squared Goodness of Fit Test. • Null hypothesis: The data follows the distribution we specify. • Alternative hypothesis: The data does not follow the distribution is we specify. If we reject the null hypothesis, we are finding evidence that the data that our observations could not have come from the specified distribution.
(1)Take a random sample of size n from the population in question (the larger the n , the better). (2)List the k values for the variable with the observed frequency (O i ) for each value. (3)Using probabilities from the hypothesized distribution, compute the expected frequency for each value, E i = p(x i )*n, from the distribution we are testing. 5

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## This note was uploaded on 01/17/2011 for the course STAT 4714 at Virginia Tech.

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Chi-squared Test - Goodness of Fit Test - Section 15.2...

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