Friday, August 14, 2009

Statistics and Theology

1. Randomness is an illusion because we can only find "randomness" via matter which itself is determined. But a "random" selection is always better than an "intelligent" selection for statistical purposes. That is, if we select what we think is the best representation of the population, we will learn less than if we leave the selection to God.

2. Central Limit Theorem: God loves the bell curve. Even if you select the numbers yourself, God's fingerprint is there hidden.

3. The bell curve - the clergy should tend to a certain level of holiness. 95% of all clergy should fall within 2 standard deviations of the average clerical holiness. Protestants think that that a few bad priests show the Church to be corrupt. If I show you 2,000 corrupt priests, would this indicate widespread corruption? That's less than 5% of the priests in the US alone. How many priests were corrupt during the Reformation? Maybe the Reformers were just bad statisticians.

4. If 100% of priests were holy, then there would be no bell curve. Even the central limit theorem would not reveal God's fingerprint. It is unnatural. Grace does not destroy nature.

5. Six Sigma theology - the average clerical holiness should be moved to a state of holiness that would leave the corrupt priests (lower spec limit) six standard deviations away. That means we cannot have more than 3.4 corrupt priests per million. A tall order.

6. The Null Hypothesis. Statistics never assert; they merely say "we don't have enough data to overturn the null hypothesis" or conversely: we do. The null hypothesis (H0) is that the Catholic Church is the Catholic Church. How much data did the Reformers need to overturn H0?

7. No list should ever have only six points.

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