# Tutorials

<!-- Register the notebooks with Sphinx -->
```{toctree}
:maxdepth: 1
:titlesonly:
:hidden:

getting_started
what_is_un
uncertainty_characterisation
uncertainty_aggregation
uncertainty_propagation
validation_assessment
```

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:gutter: 2

:::{card} Getting started
:link: getting_started
:link-type: doc
:img-top: ../_static/propagation_flowchart.png
Getting started with PyUncertainNumber and basic workflows.
:::

:::{card} What is UN?
:link: what_is_un
:link-type: doc
:img-top: ../_static/uc_diagram_smaller.png
An introduction to uncertain numbers and their representations.
:::

:::{card} Uncertainty characterisation
:link: uncertainty_characterisation
:link-type: doc
:img-top: ../_static/pbox_imprecise_measurements.png
Methods for characterising and representing uncertainty in data.
:::

:::{card} Uncertainty aggregation
:link: uncertainty_aggregation
:link-type: doc
:img-top: ../_static/distribution_expert.png
Techniques for combining multiple sources of uncertainty.
:::

:::{card} Uncertainty propagation
:link: uncertainty_propagation
:link-type: doc
:img-top: ../_static/pbox_array.png
Propagate uncertainty through computational models and functions.
:::


:::{card} Discrepancy assessment by validation 
:link: validation_assessment
:link-type: doc
:img-top: ../_static/pbox_layers_static.png
Validation of imprecise probability models.
:::

::::