testing hypothesis that data fit a given probability distribution problem: we have a sample of size...
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Testing Hypothesis That Data Fit a Given Probability Distribution
• Problem: We have a sample of size n. Determine if the data fits a probability distribution.
• Null Hypothesis, H0: The data fits the distribution.• Fact: Divide the range into k intervals. If the data fits the
distribution, then following random variable follows the chi-square distribution with k-1 degrees of freedom.
k
j j
jj
k
j
np
npn
1
2
1
2
)(
intervalkth in points ofnumber expected
)intervalkth in valuesofnumber expectedintervalkth in valuesofnumber observed(
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Testing Hypothesis That Data Fit a Given Probability Distribution
• The value of the above variable computed in a hypothesis test is called chi-square statistic.
• If chi-square statistic is too large (far in the right tail of the chi-square distribution) this is a surprising result, and it means that the evidence from the test contradicts the hypothesis that the data fit the probability distribution.
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Algorithm
1. Perform visual test first. If there is no reason to reject hypothesis proceed as follows.
2. Divide range of values in a sample into k adjacent intervals.
3. Tally the number of observations in each interval.
4. Calculate the chi-square statistic.
5. Calculate the p-value of the test.
6. Decide if the hypothesis should be rejected.
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Decision Rule
• Reject hypothesis if p-value less or equal to some low significance level (e.g. 0.05). Otherwise do not reject hypothesis.
0 10 200
0.05
0.1
0.15
dchisq x 7( )
x
Critical value (probability of exceedence 0.05)
qchisq 0.95 7( ) 14.067
Reject H0Do not reject H0