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Explained std vs var in N(mu, var) formulation.

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Some book use std, I use variance.
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Roger Labbe 2016-02-18 08:50:12 -08:00
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03-Gaussians.ipynb
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@ -1114,7 +1114,9 @@
"\n",
"$$\\text{temp} \\sim \\mathcal{N}(22,4)$$\n",
"\n",
"This is an extremely important result. Gaussians allow me to capture an infinite number of possible values with only two numbers! With the values $\\mu=22$ and $\\sigma^2=4$ I can compute the distribution of measurements for over any range."
"This is an extremely important result. Gaussians allow me to capture an infinite number of possible values with only two numbers! With the values $\\mu=22$ and $\\sigma^2=4$ I can compute the distribution of measurements for over any range.\n",
"\n",
"> Some sources use $\\mathcal N (\\mu, \\sigma)$ instead of $\\mathcal N (\\mu, \\sigma^2)$. Either is fine, they are both conventions. You need to keep in mind which form is being used if you see a term such as $\\mathcal{N}(22,4)$. In this book I always use $\\mathcal N (\\mu, \\sigma^2)$, so $\\sigma=2$, $\\sigma^2=4$ for this example."
]
},
{