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17 - Estimation of Beta probability distributions for specified alpha and beta parameters

This utility calculates summary values for Beta distributions for specified values for alpha and beta parameters.

For this analysis, two estimates were calculated. The first is for a distribution with alpha = 22.99 and beta = 3.44, and the second for a distribution with alpha = 7.39 and beta = 3.13. These values correspond to the parameters estimated in the parameter estimation example. Input values and results are summarised below.

Alpha value	Beta value	2.5% percentile	25% percentile	Median	75% percentile	97.5% percentile	Mean	Mode	Standard deviation
22.99	3.44	0.7207	0.832	0.8792	0.9176	0.9668	0.8698	0.9001	0.0642
7.39	3.13	0.41	0.6144	0.7157	0.804	0.9228	0.7025	0.75	0.1347

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Contents
1	Fixed pool size and perfect tests
2	Fixed pool size and tests with known sensitivity and specificity
3	Fixed pool size and tests with uncertain sensitivity and specificity
4	Variable pool size and perfect test
5	Pooled prevalence using a Gibbs sampler
6	Estimated true prevalence using one test (unpooled) with a Gibbs sampler
7	Estimated true prevalence using two tests (unpooled) with a Gibbs sampler
8	Sample size calculation for fixed pool size and perfect tests
9	Sample size calculation for fixed pool size and tests with known sensitivity and specificity
10	Sample size calculation for fixed pool size and tests with uncertain sensitivity and specificity
11	Simulate sampling for fixed pool size and assumed perfect test
12	Simulate sampling for fixed pool size and test with known sensitivity and specificity
13	Simulate sampling for fixed pool size and test with uncertain sensitivity and specificity
14	Simulate sampling for variable pool size and assumed perfect test
15	Demonstration of freedom using pooled testing with tests of known sensitivity and fixed pool size
16	Estimation of alpha and beta Parameters for Prior Beta distributions
17	Estimation of Beta probability distributions for specified alpha and beta parameters