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fix typo #609

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2 changes: 1 addition & 1 deletion examples/fundamentals/data_container.ipynb
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Expand Up @@ -80,7 +80,7 @@
"source": [
"## Types of Data Containers\n",
"\n",
" PyMC offers two data containers, depending on your needs: {func}`pymc.ConstantData` and {func}`pymc.MutableData`. Both will help you visualize how data fits into your model, store the data in an `InfereceData` for reproducibility, and give access to labeled dimenions. As the names suggest, however, only `MutableData` allows you to change your data. When `X` is `MutableData`, this enables out-of-sample inference tasks. When `y` is `MutableData`, it allows you to reuse the same model on multiple datasets to perform parameter recovery studies or sensitivity analysis. These abilities do, however, come with a small performance cost.\n",
" PyMC offers two data containers, depending on your needs: {func}`pymc.ConstantData` and {func}`pymc.MutableData`. Both will help you visualize how data fits into your model, store the data in an `InferenceData` for reproducibility, and give access to labeled dimenions. As the names suggest, however, only `MutableData` allows you to change your data. When `X` is `MutableData`, this enables out-of-sample inference tasks. When `y` is `MutableData`, it allows you to reuse the same model on multiple datasets to perform parameter recovery studies or sensitivity analysis. These abilities do, however, come with a small performance cost.\n",
" \n",
" In past versions of PyMC, the only data container was `pm.Data`. This container is still available for backwards compatability, but the current best practice is to use either `pm.MutableData` or `pm.ConstantData`. "
]
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