def printStats(listA, t99, t95): print("----------------------") print("N = {0}".format(len(listA))) print("Mean: {0:.4f}".format(stat.mean(listA))) print("Sample stdDev: {0:.4f}".format(stat.stdDeviation(listA))) print("99% Conf Interval: [{0:.4f}, {1:.4f}]".format( *stat.confIntervalMean(t99, listA))) print("95% Conf Interval: [{0:.4f}, {1:.4f}]".format( *stat.confIntervalMean(t95, listA)))
import statistical as stat import math data = [-0.1, -0.02, 0.1, -0.03, 0.09, 0.01, -0.05, 0.05, -0.06, 0.01, 0.03, 0.06, 0.02, -0.07, 0.03] print("Nr of datapoints: %d" %len(data)) print("Mean: %.4f" %stat.mean(data)) print("sampleVariance: %.4f" %stat.sampleVariance(data)) print("Std Dev: %.4f" %stat.stdDeviation(data)) chi1 = 48.3 chi2 = 11.2 print("Mean conf interval: %s" %(stat.confIntervalMean(1.761, data),))
def printStat(data): print("Mean: " + str(stat.mean(data))) print("Var: " + str(stat.sampleVariance(data))) print("Standard Deviation: " + str(stat.stdDeviation(data))) print("Median: " + str(stat.median(data)))
import math import statistical as stat d1 = [1, 3, 2, 2, 5, 4, 4, 3, 3] d2 = [1, 2, 4, 1, 2, 5, 2, 5, 1, 5, 5, 3] print("Mean: " + str(stat.mean(d2))) print("Var: " + str(stat.sampleVariance(d2))) print("Standard Deviation: " + str(stat.stdDeviation(d2))) print(sorted(d2))
import statistical as stat import math data = [ 1.38, 1.26, 1.52, 1.56, 1.48, 1.46, 1.30, 1.28, 1.43, 1.43, 1.55, 1.57, 1.51, 1.53, 1.68, 1.37, 1.47, 1.61, 1.49, 1.43, 1.64, 1.51, 1.60, 1.65, 1.60, 1.64, 1.51, 1.51, 1.53, 1.74 ] print(stat.sampleVariance(data)) print(stat.stdDeviation(data)) print("d) ---") print(math.sqrt(0.00833)) print(math.sqrt(0.0233))