P(X\, \leq\, k) \, =

\phi(x)=\frac{1}{\sigma \sqrt {2 \pi} } \cdot e^{-\ \ \frac{(x- \mu )^2}{2 \sigma^2}}

Normalverteilung

p = 0.41 (slider from 0 to 1, step 0.01)
n = 24 (slider from 1 to 200, step 1)
q: 1.0 - p
a = BarChart(-0.5, n + 0.5, Sequence[Binomial[n, k] * p^(k) * q^(n - k), k, 0.0, n])
k = 8 (slider from 0 to 200, step 1)
m: k
b = BarChart(-0.5, m + 0.5, Sequence[Binomial[n, k] * p^(k) * q^(n - k), k, 0.0, m])
cdf = Sum(Sequence[Binomial[n, k] * p^(k) * q^(n - k), k, 0.0, m])
Text["P(X<=k) = " + cdf]: cdf
Text1 = Text(cdf)
mu: n * p
sigma: sqrt(n * p * q)
φ(x) = 1.0 / (sigma * 2.50663) * exp(-1.0 * (x - mu)^(2.0) / (2.0 * sigma^(2.0)))
c = true
Text4 = Text("G. Roolfs")