def testOnTuples(self):
"Checks that methods also work on tuples."
self.assertAlmostEqual(basic.mean(tuple(self.dataA)), self.meanA, 5)
self.assertAlmostEqual(basic.mean(tuple(self.dataB)), self.meanB, 5)
self.assertAlmostEqual(basic.stddev(tuple(self.dataA)),
self.stddevA, 5)
self.assertAlmostEqual(basic.stddev(tuple(self.dataB)),
self.stddevB, 5)
def testOnTuples(self):
"Checks that methods also work on tuples."
self.assertAlmostEqual(basic.mean(tuple(self.dataA)), self.meanA, 5)
self.assertAlmostEqual(basic.mean(tuple(self.dataB)), self.meanB, 5)
self.assertAlmostEqual(basic.stddev(tuple(self.dataA)), self.stddevA,
5)
self.assertAlmostEqual(basic.stddev(tuple(self.dataB)), self.stddevB,
5)
from basic import mean, median, mode _ = int(input()) arr = sorted(map(int, input().split())) print(mean(arr)) print(median(arr)) print(mode(arr))
def testBasicStats(self):
"Test that the basic stats method works."
meanA, stddevA = basic.basic_stats(self.dataA)
self.assertAlmostEqual(meanA, basic.mean(self.dataA))
self.assertAlmostEqual(stddevA, basic.stddev(self.dataA))
def testMean(self):
"Check that mean works as expected."
self.assertAlmostEqual(basic.mean(self.dataA), self.meanA, 5)
self.assertAlmostEqual(basic.mean(self.dataB), self.meanB, 5)
def least_squares(x, y): beta = correlation(x, y) * standart_deviation(y) / standart_deviation(x) alpha = mean(y) - beta * mean(x) return alpha, beta
def testBasicStats(self):
"Test that the basic stats method works."
meanA, stddevA = basic.basic_stats(self.dataA)
self.assertAlmostEqual(meanA, basic.mean(self.dataA))
self.assertAlmostEqual(stddevA, basic.stddev(self.dataA))
def testMean(self):
"Check that mean works as expected."
self.assertAlmostEqual(basic.mean(self.dataA), self.meanA, 5)
self.assertAlmostEqual(basic.mean(self.dataB), self.meanB, 5)