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Small doc fixes (#25)
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docs/examples/azcausal.ipynb

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{
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"cell_type": "markdown",
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"id": "9",
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"metadata": {
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"title": "As before, we may now go about estimating the treatment. However, this"
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},
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"metadata": {},
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"source": [
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"time we see that the delta between the estaimted and true effect is much larger than\n",
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"As before, we may now go about estimating the treatment. However, this time we see that the delta between the estimated and true effect is much larger than\n",
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"before."
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]
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},

docs/examples/basic.ipynb

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{
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"cell_type": "markdown",
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"id": "3",
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"title": "Simulating a dataset is as simple as specifying a `Config` object and"
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},
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"metadata": {},
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"source": [
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"then invoking the `simulate` function. Once simulated, we may visualise the data\n",
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"Simulating a dataset is as simple as specifying a `Config` object and then invoking the `simulate` function. Once simulated, we may visualise the data\n",
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"through the `plot` function."
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]
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},
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"variation. In a follow-up notebook, we show how these datasets may be integrated with\n",
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"Amazon's own AZCausal library to compare the effect estimated by a model with the true\n",
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"effect of the underlying data generating process. A link to this notebook is\n",
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"[here](http://localhost:9998/causal-validation/examples/azcausal/)."
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"[here](https://amazon-science.github.io/causal-validation/examples/azcausal/)."
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]
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}
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],

docs/examples/placebo_test.ipynb

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"datasets = DatasetContainer([data, complex_data], names=[\"Simple\", \"Complex\"])\n",
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"PlaceboTest([model, did_model], datasets).execute().summary()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "14",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "15",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {

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