Normal Distribution
\[ f(x,μ,σ)=\frac{1}{σ\sqrt{2π}}\ e^{\ −\frac{(x−μ)^2}{2σ^2}} \]
\[ f(x,μ,σ)=\frac{1}{σ\sqrt{2π}}\ e^{\ −\frac{(x−μ)^2}{2σ^2}} \]
\[f(x,μ,σ)=\frac{1}{n}\]
\[f(x) = \frac{x^{k/(2-1)}\ e^{-x/2}}{2^{k/2}\ \Gamma(k/2)}\] \[\huge\chi^2 = \large\sum_{i=0}^{n} \frac{\left(x_{obs} - x_{exp}\right)^2}{x_{exp}}\] 1. Requires degrees of freedom (df)
\[f(x)=\left(\frac{x_m}{x}\right)^\alpha\] * 80/20 Rule
Success #stdin #stdout 0.23s 42812KB
Call:
glm(formula = y ~ x)
Deviance Residuals:
Min 1Q Median 3Q Max
-8.4184 -0.5135 0.0514 0.3308 5.0336
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.04620 0.22230 0.208 0.835
x 1.00223 0.00222 451.541 <2e-16 ***
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for gaussian family taken to be 0.5019413)
Null deviance: 102841.49 on 999 degrees of freedom
Residual deviance: 500.94 on 998 degrees of freedom
AIC: 2152.6
Number of Fisher Scoring iterations: 2
