Normal Distribution
variable
$$\mathrm{Normal}(\mu, \sigma^2)$$
pdf
$$f(z) = \frac{1}{\sqrt{2 \pi \sigma^2}} \ \exp \left( -\frac{(z-\mu)^2}{2 \sigma^2} \right)$$
mean
$$\mu$$
variance
$$\sigma^2$$
mgf
$$m(t) = \exp \left( \mu t + \frac{\sigma^2 t^2}{2} \right)$$
probabilities
confidence interval
Student's T Distribution
variable
$$\mathrm{T}_\nu$$
pdf
$$f(z) = \frac{\Gamma \left( \frac{\nu+1}{2} \right)}{\sqrt{\nu \pi} \ \Gamma \left( \frac{\nu}{2} \right)} \ \left( 1 + \frac{z^2}{\nu} \right)^{-\frac{\nu+1}{2}}$$
mean
$$0$$
variance
$$\frac{\nu}{\nu-2}$$
mgf
$$E[X^{2n}] = \frac{\Gamma \left( \frac{\nu + 1}{2} \right) \ \Gamma \left( \nu - n \right)}{\sqrt{\pi} \ \Gamma \left( \frac{\nu}{2} \right)}$$
probabilities
confidence interval
Chi-Squared Distribution
variable
$$\chi_\nu^2$$
pdf
$$f(z) = \frac{1}{\Gamma \left( \frac{\nu}{2} \right) \ 2^{\frac{\nu}{2}}} \ z^{\frac{\nu}{2} - 1} \ \exp \left( -\frac{z}{2} \right)$$
mean
$$\nu$$
variance
$$2 \nu$$
mgf
$$m(t) = \left( \frac{1}{1-2t} \right)^{\frac{\nu}{2}}$$
probabilities
confidence interval