def get_prob_over(data_by_row, mus):
"""
Return array of arrays
column[i] = [probability_above]
"""
probability_above_mu = []
size = len(data_by_row)
by_col = hw3.transpose_array(data_by_row)
for col in range(len(by_col)):
total_over = 0
column = by_col[col]
mu_col = mus[col]
var_col = utils.variance(by_col[col], size)
for row in range(len(column)):
if column[row] > mu_col:
total_over += 1
probability_above_mu.append(float(total_over)/size)
return probability_above_mu
def summary(array):
""" returns mean and variance"""
return [utils.average(array), utils.variance(array, len(d))]
