add link to wikipedia page for Bayes Factors

Author: drbenvincent

examples/howto/hypothesis_testing.ipynb

@@ -528,7 +528,7 @@
    "source": [
     "### Bayes Factors\n",
     "\n",
-    "Bayes Factors provide a Bayesian alternative to classical hypothesis tests, allowing you to weigh evidence for one hypothesis relative to another. In the simplest case—testing whether $\\mu=0$ versus $\\mu \\neq 0$ — the Bayes Factor (BF) tells you how much more (or less) likely your observed data are under the model where $\\mu=0$ than under the model where $\\mu$ is free to vary.\n",
+    "[Bayes Factors](https://en.wikipedia.org/wiki/Bayes_factor) provide a Bayesian alternative to classical hypothesis tests, allowing you to weigh evidence for one hypothesis relative to another. In the simplest case—testing whether $\\mu=0$ versus $\\mu \\neq 0$ — the Bayes Factor (BF) tells you how much more (or less) likely your observed data are under the model where $\\mu=0$ than under the model where $\\mu$ is free to vary.\n",
     "\n",
     "Intuitively, the Bayes Factor can be understood by comparing the density of $\\mu$ at zero before and after observing the data. Before collecting data, you have a prior belief about $\\mu$. This prior density at $\\mu=0$ represents how plausible zero was considered initially. After seeing the data, you update these beliefs to get the posterior distribution. The posterior density at $\\mu=0$ indicates how plausible zero remains given the evidence. The ratio of these densities—the Savage-Dickey ratio—is closely related to the Bayes Factor. If the data make \n",
     "$\\mu=0$ more plausible relative to your initial belief, the Bayes Factor will favor  $\\mu=0$. If the data diminish the credibility of $\\mu=0$, the Bayes Factor will favor $\\mu\\neq0$\n",

examples/howto/hypothesis_testing.myst.md

@@ -179,7 +179,7 @@ In our case, we would remain undecided because the HDI does not fall entirely ou
 
 ### Bayes Factors
 
-Bayes Factors provide a Bayesian alternative to classical hypothesis tests, allowing you to weigh evidence for one hypothesis relative to another. In the simplest case—testing whether $\mu=0$ versus $\mu \neq 0$ — the Bayes Factor (BF) tells you how much more (or less) likely your observed data are under the model where $\mu=0$ than under the model where $\mu$ is free to vary.
+[Bayes Factors](https://en.wikipedia.org/wiki/Bayes_factor) provide a Bayesian alternative to classical hypothesis tests, allowing you to weigh evidence for one hypothesis relative to another. In the simplest case—testing whether $\mu=0$ versus $\mu \neq 0$ — the Bayes Factor (BF) tells you how much more (or less) likely your observed data are under the model where $\mu=0$ than under the model where $\mu$ is free to vary.
 
 Intuitively, the Bayes Factor can be understood by comparing the density of $\mu$ at zero before and after observing the data. Before collecting data, you have a prior belief about $\mu$. This prior density at $\mu=0$ represents how plausible zero was considered initially. After seeing the data, you update these beliefs to get the posterior distribution. The posterior density at $\mu=0$ indicates how plausible zero remains given the evidence. The ratio of these densities—the Savage-Dickey ratio—is closely related to the Bayes Factor. If the data make 
 $\mu=0$ more plausible relative to your initial belief, the Bayes Factor will favor  $\mu=0$. If the data diminish the credibility of $\mu=0$, the Bayes Factor will favor $\mu\neq0$