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SD to BSE doc update + regenerate .py with nbdev 3.3.1
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dabest/_api.py

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"""Loading data and relevant groups"""
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"""Loading data and relevant groups
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Docs: https://acclab.github.io/DABEST-python/API/load.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/load.ipynb.
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dabest/_bootstrap_tools.py

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"""Docs: https://acclab.github.io/DABEST-python/API/bootstrap.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/bootstrap.ipynb.
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# %% auto #0

dabest/_dabest_object.py

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"""Main class for estimating statistics and generating plots."""
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"""Main class for estimating statistics and generating plots.
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Docs: https://acclab.github.io/DABEST-python/API/dabest_object.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/dabest_object.ipynb.
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dabest/_delta_objects.py

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"""Auxiliary delta classes for estimating statistics and generating plots."""
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"""Auxiliary delta classes for estimating statistics and generating plots.
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Docs: https://acclab.github.io/DABEST-python/API/delta_objects.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/delta_objects.ipynb.
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dabest/_effsize_objects.py

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"""The auxiliary classes involved in the computations of bootstrapped effect sizes."""
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"""The auxiliary classes involved in the computations of bootstrapped effect sizes.
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Docs: https://acclab.github.io/DABEST-python/API/effsize_objects.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/effsize_objects.ipynb.
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group_summaries : ['mean_sd', 'median_quartiles', 'None'], default "mean_sd".
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Plots the summary statistics for each group. If 'mean_sd', then
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the mean and standard deviation of each group is plotted as a
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notched line beside each group. If 'median_quantiles', then the
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notched line beside each group. For proportion and Sankey plots, this error is the binomial standard error (BSE), sqrt(p(1-p)/n), not the SD. If 'median_quantiles', then the
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median and 25th and 75th percentiles of each group is plotted
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instead. If 'None', the summaries are not shown.
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fig_size : tuple, default None

dabest/_stats_tools/confint_1group.py

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"""A range of functions to compute bootstraps for a single sample."""
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"""A range of functions to compute bootstraps for a single sample.
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Docs: https://acclab.github.io/DABEST-python/API/confint_1group.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/API/confint_1group.ipynb.
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dabest/_stats_tools/confint_2group_diff.py

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"""A range of functions to compute bootstraps for the mean difference"""
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"""A range of functions to compute bootstraps for the mean difference
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Docs: https://acclab.github.io/DABEST-python/API/confint_2group_diff.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/API/confint_2group_diff.ipynb.
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dabest/_stats_tools/effsize.py

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"""A range of functions to compute various effect sizes."""
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"""A range of functions to compute various effect sizes.
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Docs: https://acclab.github.io/DABEST-python/API/effsize.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/API/effsize.ipynb.
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dabest/_stats_tools/precompile.py

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"""A tool to pre-compile Numba functions for speeding up DABEST bootstrapping"""
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"""A tool to pre-compile Numba functions for speeding up DABEST bootstrapping
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Docs: https://acclab.github.io/DABEST-python/API/precompile.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/API/precompile.ipynb.
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dabest/forest_plot.py

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"""Creating forest plots from contrast objects."""
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"""Creating forest plots from contrast objects.
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Docs: https://acclab.github.io/DABEST-python/API/forest_plot.html.md"""
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/forest_plot.ipynb.
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