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Desviación típica (σ)

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μ-σ

μ

μ+σ

P(x≤k_{1})

P(X≥k_{1})

k_{1}≤x≤k_{2}

N(0,1)

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Problema inverso

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a = -1.3877787807814457E-16 (slider from -5 to 5, step 0.1)
b = 1.0000000000000002 (slider from 0.05 to 5, step 0.05)
f(x) = (1 / ((b * sqrt((2 * π)))) * ℯ^(((-((x - a) / b)^(2))) / 2))
c = Segment((a, 0), (a, f(a)))
d = Segment((a + b, 0), (a + b, f(a + b)))
e = Segment((a - b, 0), (a - b, f(a - b)))
C: (a + b, f(a + b))
B: (a - b, f(a - b))
A: (a, f(a))
D: (a - b, 0)
E: (a + b, 0)
F: (a, 0)
g = false
h = false
k_{1} = -0.9 (slider from -5 to 5, step 0.1)
k_{2} = 1.6 (slider from k_{1} to 5, step 0.1)
p1 = IntegralBetween(f, 0, -50, k_{1})
i1 = false
texto6: "P(x≤" + k_{1} + ")=" + p1 + ""
p2 = IntegralBetween(f, 0, k_{1}, 50)
i2 = false
i3 = false
p3 = IntegralBetween(f, 0, k_{1}, k_{2})
texto8: "P(x≥" + k_{1} + ")=" + p2 + ""
texto9: "P(" + k_{1} + "≤x≤" + k_{2} + ")=" + p3 + ""
inv = false
p = 0.4000000000000001 (slider from 0.01 to 1, step 0.01)
j = InverseNormal(0, 1, p)
k = IntegralBetween(f, 0, -50, j)
i = (-0.019999999999999997, 1)
texto10: "" + p + "=P(X<" + j + ")"