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monte carlo update
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zamanlh committed Aug 6, 2012
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Expand Up @@ -69,13 +69,16 @@ Monte Carlo test. In this case we know this data came from a normal distribution
#output
[1] "p-value = 0.00105"

![Monte Carlo](https://github.com/briandconnelly/BEACONToolkit/raw/master/analysis/doc/figures/monte_carlo.png)

We can compare our simulated p-value to the t-test closed form solution and see they are quite similar.

#compare this to the t-test p-value
t.test(cold_effect, alternative="greater")

#output
t = 3.0718, df = 49, p-value = 0.001734

![Monte Carlo](https://github.com/briandconnelly/BEACONToolkit/raw/master/analysis/doc/figures/monte_carlo.png)


### What 95% confidence intervals are

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