compute t-distribution confidence interval

t_confidence_interval.py

from scipy.stats import t
import numpy

def sampleStdev(samples):
    mean = numpy.mean(samples)
    squareSamples = [ numpy.power(x - mean, 2) for x in samples]
    sumSqr = numpy.sum(squareSamples)
    sampleStdev = numpy.sqrt(sumSqr / (len(samples) - 1))
    return sampleStdev

def tConfidenceInterval(alpha, sampleSize, stdev):
    degreeOfFreedom = sampleSize - 1
    tCritical = t.ppf(1 - alpha/2, degreeOfFreedom)
    confidenceInterval = tCritical * stdev / numpy.sqrt(sampleSize)
    return confidenceInterval

def computeTConfidenceInterval(alpha, samples):
    stdev = sampleStdev(samples)
    print stdev
    return tConfidenceInterval(alpha, len(samples), stdev)

samples = [1.5, 2, 3, 2.5, 2.75, 2.25, 2.25, 2, 1.75, 2, 1.5, 3, 1.99, 2.22, 2.77, 3.1]

print computeTConfidenceInterval(0.05, samples)