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add references + info about HDI+ROPE criteria
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examples/howto/hypothesis_testing.ipynb

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"This shows that there is only a 2.6% chance that the mean is within the chosen ROPE."
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},
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{
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"cell_type": "markdown",
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"id": "de465219",
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"metadata": {},
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"source": [
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"{ref}`kruschke2018rejecting` outlines the HDI+ROPE decision rule, which is summarised in the figure taken from that paper:\n",
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"\n",
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"![](hdi_plus_rope_decision_rule.png)\n",
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"\n",
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"In our case, we would remain undecided because the HDI does not fall entirely outside nor within the ROPE."
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]
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"cell_type": "markdown",
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"* Authored by [Benjamin T. Vincent](https://github.com/drbenvincent) in December, 2024."
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]
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{
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"cell_type": "markdown",
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"id": "2b3bbd1b",
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"metadata": {},
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"source": [
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"## References\n",
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":::{bibliography}\n",
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":filter: docname in docnames\n",
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":::"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1aec5c13",

examples/howto/hypothesis_testing.myst.md

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{ref}`kruschke2018rejecting` outlines the HDI+ROPE decision rule, which is summarised in the figure taken from that paper:
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![](hdi_plus_rope_decision_rule.png)
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In our case, we would remain undecided because the HDI does not fall entirely outside nor within the ROPE.
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### Bayes Factors
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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.
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## References
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:::{bibliography}
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:filter: docname in docnames
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:::
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## Watermark
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```{code-cell} ipython3

examples/references.bib

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doi = {10.1214/21-BA1287},
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URL = {https://doi.org/10.1214/21-BA1287}
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}
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@article{kruschke2010believe,
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title={What to believe: Bayesian methods for data analysis},
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author={Kruschke, John K},
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journal={Trends in cognitive sciences},
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volume={14},
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number={7},
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pages={293--300},
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year={2010},
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publisher={Elsevier}
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}
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@article{kruschke2018rejecting,
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title={Rejecting or accepting parameter values in Bayesian estimation},
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author={Kruschke, John K},
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journal={Advances in methods and practices in psychological science},
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volume={1},
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number={2},
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pages={270--280},
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year={2018},
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publisher={Sage Publications Sage CA: Los Angeles, CA}
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}

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