<jupyter_start><jupyter_text>44.2.1  Find $P(0.1 < U <0.5)$<jupyter_code>from modules.normal import Normal
from scipy.stats import norm

nd = Normal(mu=0, sigma=1)
low_area = nd.cdf(0.1)
low_area
high_area = 1 - nd.cdf(0.5)
high_area
1 - low_area - high_area
X = np.linspace(-3, 3)
Y = list(map(nd.cdf, X))
plt.plot(X, Y)<jupyter_output><empty_output><jupyter_text>Opgave 44.2.2 Udregn $P(Y_1 < 275)$<jupyter_code>mu = 350
sigma_sq = 12365
sigma = np.sqrt(12365)

nd = Normal(mu, sigma)
nd.cdf(275)<jupyter_output><empty_output><jupyter_text>Udregn $P(Y_1 > 425)$<jupyter_code>nd = Normal(mu, sigma)
1 - nd.cdf(425)
nd.cdf(275)
0.193 /0.25<jupyter_output><empty_output><jupyter_text>Opgave 44.2.3  mængden A<jupyter_code>sd = SetDraw((-1, 5),(-1, 5))
def c1(x,y):
    if (0 <= x + y <= 1) and (x>0) and (y>0):
        return True
    else:
        return False
sd.add_condition(c1)
x, y = sd.points()
plt.scatter(x, y)
1 - np.exp(-3) + 3*np.exp(-2)*(np.exp(1)- 1)<jupyter_output><empty_output>
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