n

β

p von

p bis

p

h von

h bis

*σ

exakt

Näherung

Abschätzung

h

exakt

Abschätzung

Konfidenz

Prognose

veränderbar

σ

ß

G4: 0.954499736103643
B9 = 0.3177723943141642
B1: 100
B4: 0.3
B2: G4
β: B2
A = (0, 0)
B = (1, 0)
f = Segment(A, B)
h: B4
k_1 = InverseNormal(0, 1, (β + 1) / 2)
n: B1
u_1: (k_1^(2) / ((2 * n)) + h - (k_1 * sqrt(k_1^(2) / 4 / n^(2) + (h * (1 - h) / n)))) / (k_1^(2) / n + 1)
o_1: (k_1^(2) / ((2 * n)) + h + (k_1 * sqrt(k_1^(2) / 4 / n^(2) + (h * (1 - h) / n)))) / (k_1^(2) / n + 1)
r_o: o_1 - h
f_+(x) = x + (k_1 * sqrt(((x * (1 - x))) / n))
f_-(x) = x - (k_1 * sqrt(((x * (1 - x))) / n))
U: (u_1, h)
O: (o_1, h)
rH: (0, B4)
OO: (1, h)
i = Segment(rH, OO)
j = Segment(U, O)
PP: (1, 0)
k = Segment(A, PP)
Wk: (B9, 0)
l = Segment((x(Wk), 0), (x(Wk), 1))
m = Segment((x(Wk), f_-(x(Wk))), (x(Wk), f_+(x(Wk))))
H: (0, h)
B5: u_1
B6: o_1
B11: f_+(B9)
B10: f_-(B9)
C2: k_1
C5: f_-(B4)
C6: f_+(B4)
D6: B4 + C2 / 2 / sqrt(B1)
D5: B4 - C2 / 2 / sqrt(B1)
C10: B9 - C2 / 2 / sqrt(B1)
C11: B9 + C2 / 2 / sqrt(B1)
F3: 1
G3: 0.682689492137087
F4: 2
F5: 3
G5: 0.997300203936741