0.558, 0.641, 0.302, 0.091, -0.389, 1.997, 0.475, 0.226, 0.404, -1.476,
0.051, 0, 0, 0
]
student_answers = []
import numpy as np
x, y = np.loadtxt("results.csv",
delimiter=",",
usecols=(0, 1),
unpack=True,
skiprows=1)
x = list(x)
y = list(y)
test_case_1 = A2.mean(x)
student_answers.append(test_case_1)
test_case_2 = A2.median(x)
student_answers.append(test_case_2)
test_case_3 = A2.standard_deviation(x)
student_answers.append(test_case_3)
test_case_4 = A2.variance(x)
student_answers.append(test_case_4)
test_case_5 = A2.skewness(x)
student_answers.append(test_case_5)
test_case_6 = A2.kurtosis(x)
actual_answers = [
0.558, 0.641, 0.302, 0.091, -0.389, 1.997, 0.475, 0.226, 0.404, -1.476,
0.051, 0, 0, 0
]
student_answers = []
x, y = np.loadtxt(
"C:/Users/RISHABH AGARWAL/Downloads/SEM 5/CS384-Python/CS384_1801EE40/Assignment2/results.csv",
delimiter=",",
usecols=(0, 1),
unpack=True,
skiprows=1)
x = list(x)
y = list(y)
test_case_1 = A2.mean(x)
student_answers.append(test_case_1)
test_case_2 = A2.median(x)
student_answers.append(test_case_2)
test_case_3 = A2.standard_deviation(x)
student_answers.append(test_case_3)
test_case_4 = A2.variance(x)
student_answers.append(test_case_4)
test_case_5 = A2.skewness(x)
student_answers.append(test_case_5)
test_case_6 = A2.kurtosis(x)