# TEXAS Interactive Tutorial

Welcome to the TEXAS interactive tutorial — a hands-on guide for paleoceanographers and paleolimnologists who want to understand **how and why** TEXAS reconstructs past temperatures from GDGTs, without needing a statistics background.

## Who this is for

You know your proxies. You've worked with TEX86 or Ring Index data, you understand what GDGTs are and why they record temperature — but the Bayesian machinery behind TEXAS may feel like a black box. This tutorial is designed to open that box, one concept at a time, using interactive visualizations rather than equations.

## What you will learn

| Module | Topic | Key question answered |
|--------|-------|----------------------|
| 1 | What is a prior? | How do we encode what we already know before looking at data? |
| 2 | Bayesian updating | How does new data change our beliefs? |
| **3** | **The calibration curve** | **What do the four curve parameters actually control?** |
| 4 | What MCMC does | Why do we get 4,000 answers instead of one? |
| 5 | Reading your results | How do I interpret credible intervals on a temperature reconstruction? |

## How to use these notebooks

Each module is a Jupyter notebook. Run cells top to bottom. The interactive widgets (sliders, dropdowns) require a live kernel — they will not work in a static PDF or HTML export, but will work in JupyterLab or VS Code with the Jupyter extension.

```{tip}
Start with Module 3 if you want to build intuition for the calibration curve right away. Modules 1 and 2 are foundational but not required to understand Module 3.
```