def confidence_interval(data, percentile, number_of_tails):
"""
Computes confidence interval for the
mean of the given data covering the probability given by the
variable percentile.
* data specifies the given data.
* precentile gives the probability that the mean of the data is in
the confidence interval.
* number_of_tails gives the number of tails of the normal distribution
to be considered.
"""
square = math.pow(len(data), 0.5)
mean = statchar.aritmetic_mean(data)
std_dev = statchar.std_dev_corrected(data)
dist = distributions.NormalDistribution(0, 1)
if number_of_tails == 2:
alfa = (1-percentile)/2
c = distributions.find_percentile(1-alfa, dist.cdf)
left = mean - c*std_dev/square
right = mean + c*std_dev/square
return left, right
elif number_of_tails == 1:
alfa = percentile
c = distributions.find_percentile(alfa, dist.cdf)
SEM = statchar.std_error_of_mean(data)
left = mean
right = mean + c*SEM/square
return right
def test_results(self):
list_1 = [1, 2, 3, 4, 5]
result = statchar.std_dev_corrected(list_1)
self.assertTrue(1.581 < result and result < 1.582)