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{\displaystyle P(Z\in [-z,z])=P(-z\leq Z\leq z)=\int _{-z}^{+z}\varphi (t)\mathrm {d} t=\Phi (z)-\Phi (-z)=\Phi (z)-(1-\Phi (z))=2\Phi (z)-1\,.}
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Normalverteilung – Wikipedia
{\displaystyle \Phi (-z)=P[Z\leq -z]=1-P[Z\geq -z]=1-P[Z\leq z]=1-\Phi (z)}
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Κανονική κατανομή - Βικιπαίδεια
{\displaystyle P(\mu -z\sigma \leq X\leq \mu +z\sigma )=P\left(-z\leq {\frac {X-\mu }{\sigma }}\leq z\right)=P(-z\leq Z\leq z)\;.}
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Normalverteilung – Wikipedia
{\displaystyle {\begin{aligned}L(z)&=\int _{z}^{\infty }(u-z)\varphi (u)\,du=\int _{z}^{\infty }[1-\Phi (u)]\,du\\[5pt]L(z)&\approx {\begin{cases}0.4115\left({\dfrac {p}{1-p}}\right)-z,&p<1/2,\\\\0.4115\left({\dfrac {1-p}{p}}\right),&p\geq 1/2.\end{cases}}\\[5pt]{\text{or, equivalently,}}\\L(z)&\approx {\begin{cases}0.4115\left\{1-\log \left[{\frac {p}{1-p}}\right]\right\},&p<1/2,\\\\0.4115{\dfrac {1-p}{p}},&p\geq 1/2.\end{cases}}\end{aligned}}}
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Normal distribution - Wikipedia
{\displaystyle m(z_{1},z_{2},...,z_{s})=\mathrm {e} ^{\left(\mathbf {z} ^{T}\mathbf {\mu } +{\frac {\mathbf {z} ^{T}\mathbf {C} \mathbf {z} }{2}}\right)}}
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Normální rozdělení – Wikipedie
Understanding the Z-Transform II: Understanding z and the Z-Plot
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Understanding the Z-Transform II: Understanding...
Gen Z in the Workplace: A Gen Z Perspective from an HR Professional and Mother of Gen Z
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Gen Z in the Workplace: A Gen Z Perspective fro...
{\displaystyle \left(\varprojlim \mathbb {Z} /p^{n}\right)\otimes _{\mathbb {Z} }\mathbb {Q} =\mathbb {Z} _{p}\otimes _{\mathbb {Z} }\mathbb {Q} =\mathbb {Z} _{p}\left[p^{-1}\right]=\mathbb {Q} _{p}}
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{\displaystyle \left(\varprojlim \mathbb {Z} /p...
{\displaystyle \mathbb {Z} /p\mathbb {Z} \otimes _{\mathbb {Z} }\mathbb {Z} /p\mathbb {Z} }
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{\displaystyle \mathbb {Z} /p\mathbb {Z} \otime...
{\displaystyle p=P(X\in [\mu -z\sigma ,\mu +z\sigma ])=P(Z\in [-z,z])}
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Normalverteilung – Wikipedia
{\displaystyle {\begin{array}{rrcl}\varphi :&\mathbb {C} &\rightarrow &\mathbb {C} \\&z&\mapsto &\displaystyle \varphi (z)={\frac {1}{\sqrt {2\pi }}}\cdot e^{-{\frac {z^{2}}{2}}}={\frac {1}{\sqrt {2\pi }}}\cdot \underbrace {\sum _{n=0}^{\infty }{\frac {(-1)^{n}}{n!\cdot 2^{n}}}\cdot z^{2n}} _{=e^{-{\frac {z^{2}}{2}}}}\end{array}}}
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Normalverteilung – Wikipedia
{\displaystyle {\frac {z''}{(1+z'^{2})^{3/2}}}+{\frac {z'}{r(1+z'^{2})^{{1}/{2}}}}=\Delta p^{*}-z(r).}
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Young–Laplace equation - Wikipedia
{\displaystyle {\frac {\mathbb {C} [x,y,z]}{(f)}}\otimes _{\mathbb {C} [x,y,z]}{\frac {\mathbb {C} [x,y,z]}{(g)}}\cong {\frac {\mathbb {C} [x,y,z]}{(f,g)}}}
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{\displaystyle {\frac {\mathbb {C} [x,y,z]}{(f)...
{\displaystyle \mathbb {Z} /p\mathbb {Z} \otimes \mathbb {Z} /q\mathbb {Z} =0.}
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{\displaystyle \mathbb {Z} /p\mathbb {Z} \otime...
{\displaystyle \mathbb {Z} /n\otimes _{\mathbb {Z} }\mathbb {Z} /m=\mathbb {Z} /{\gcd(n,m)}}
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{\displaystyle \mathbb {Z} /n\otimes _{\mathbb ...
{\displaystyle {P}(-z<Z\leq z)=2F(z)-1}
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Нормална распределба — Википедија
{\displaystyle \ 1-\Phi (z)=\int _{z}^{\infty }{\frac {1}{\sqrt {2\pi }}}e^{-x^{2}/2}dx\approx {\frac {1}{z+1/2}}e^{-z^{2}/2}}
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התפלגות נורמלית – ויקיפדיה
{\displaystyle \psi _{X}(t)=\operatorname {E} (e^{it(\sigma Z+\mu )})=\operatorname {E} (e^{it\sigma Z}e^{it\mu })=e^{it\mu }\operatorname {E} (e^{it\sigma Z})=e^{it\mu }\psi _{Z}(\sigma t)=\exp \left(it\mu -{\tfrac {1}{2}}\sigma ^{2}t^{2}\right)}
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Normalverteilung – Wikipedia
[POV : Gen Z] The Real Tea: How Gen Z Is Changing the Workplace Vibe ☕
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Cracking the Gen Z Code : Why Brands Need to Rethink Their Approach to Gen Z.
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