One-page reference for common positive-support distributions plus Normal. Each box shows: PDF, CDF, key moments, quantiles, and **Excel** formulas.
Shape–Scale \(X\sim \mathrm{Gamma}(\alpha,\theta)\): PDF \(f(x)=\dfrac{x^{\alpha-1}e^{-x/\theta}}{\Gamma(\alpha)\theta^\alpha}\), \(E[X]=\alpha\theta\), \(\mathrm{Var}(X)=\alpha\theta^2\).
Shape–Rate \(X\sim \mathrm{Gamma}(\alpha,\lambda)\): PDF \(f(x)=\dfrac{\lambda^\alpha x^{\alpha-1}e^{-\lambda x}}{\Gamma(\alpha)}\), \(E[X]=\alpha/\lambda\), \(\mathrm{Var}(X)=\alpha/\lambda^2\).
        =NORM.DIST(x, mean, sd, TRUE/FALSE)
        =NORM.S.DIST(z, TRUE/FALSE)
        =NORM.INV(p, mean, sd), =NORM.S.INV(p)
      
        =LOGNORM.DIST(x, theta, omega, TRUE/FALSE)
        =LOGNORM.INV(p, theta, omega)
      
=EXPON.DIST(x, lambda, TRUE/FALSE) (lambda = 1/mean)
        =GAMMA.DIST(x, alpha, theta, TRUE/FALSE)   (theta = scale)
        =GAMMA.INV(p, alpha, theta)
      
        =WEIBULL.DIST(x, alpha, beta, TRUE/FALSE)   (alpha=shape β, beta=scale δ)
        =WEIBULL.INV(p, alpha, beta)
      
        =BETA.DIST(x, alpha, beta, TRUE/FALSE, [A], [B])
        =BETA.INV(p, alpha, beta, [A], [B])
      
        =CHISQ.DIST(x, df, TRUE/FALSE)
        =CHISQ.DIST.RT(x, df)   (right tail)
        =CHISQ.INV(p, df), =CHISQ.INV.RT(p, df)
      
Parameter reminders: Excel’s “beta” for Gamma/Weibull means **scale**.
    For Gamma with rate \(\lambda\), use theta = 1/lambda. For Exponential with mean \(\delta\),
    use lambda = 1/δ. For Beta on \([A,B]\), pass [A],[B]; omit for standard \([0,1]\).