See All: Questions For Statistics From Khan Academy
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1:
Code:
mean = 170.4 sd = 10 l = 145 lz = (l - mean) / sd print(lz) import statistics lz_area = statistics.NormalDist(mu=0, sigma=1).cdf(lz) print(lz_area) h = 171 hz = (h - mean) / sd print(hz) hz_area = statistics.NormalDist().cdf(hz) area_req = round(hz_area - lz_area,4) print(area_req)
2:
mean = 80 sd = 9 proportion = 0.4 import statistics z = statistics.NormalDist().inv_cdf(proportion) print(z) x = z * sd + mean print(x)
3:
Code:
mean = 13.1 sd = 1.5 sd1 = (mean - sd, mean + sd) print(sd1) sd2 = (mean - 2 * sd, mean + 2 * sd) print(sd2) sd3 = (mean - 3 * sd, mean + 3 * sd) print(sd3) sd2_area = 0.95 sd3_area = 0.997 area_req = (sd3_area - sd2_area) / 2 print(area_req) percentage_wise = round(area_req * 100, 4) print(percentage_wise) out = """ (11.6, 14.6) (10.1, 16.1) (8.6, 17.6) 0.02350000000000002 2.35 """
4:
Code:
b = 2 h = 0.6 area = 0.5 * b * h percentage_of_area = area * 100 print(percentage_of_area)
5:
Code:
mean_sales = 8000
sd_sales = 1500
mean_salary = 2000 + 0.3 * mean_sales
sd_salary = sd_sales * 0.3
print("mean_salary, sd_salary")
print(mean_salary, sd_salary)
6:
7:
area = 1 b = 6 h = area * 2 / b print(h)
8:
def area_of_trapezium(b1, b2, h):
return 0.5 * (b1 + b2) * h
b1 = 0.5
b2 = 0.75
h = 1
a = area_of_trapezium(b1, b2, h)
print(a)
print(round(a*100, 4))
b1 = 0.25
b2 = 0.5
h = 1
a = area_of_trapezium(b1, b2, h)
print(a)
print(round(a*100, 4))
9:
10:
mean = 1497 sd = 322 proportion = 0.85 import statistics z = statistics.NormalDist().inv_cdf(proportion) x = z * sd + mean print(round(x, 4))
See All: Questions For Statistics From Khan Academy
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