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    "# Tutorials\n",
    "\n",
    "Jupyter Notebooks for tutorials of `scores`.\n",
    "\n",
    "\n",
    "Firstly run [Data Fetching](./First_Data_Fetching.ipynb) to fetch the data needed for some later notebooks\n"
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   ]
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    "\n",
    "## Continuous\n",
    "- [Additive Bias and Multiplicative Bias](./Additive_and_multiplicative_bias.ipynb)\n",
    "- [MAE](./Mean_Absolute_Error.ipynb)\n",
    "- [RMSE](./Root_Mean_Squared_Error.ipynb)\n",
    "- [MSE](./Mean_Squared_Error.ipynb)\n",
    "- [Pearson's Correlation](./Pearsons_Correlation.ipynb)\n",
    "- [Quantile Loss](./Quantile_Loss.ipynb)\n",
    "- [Murphy Diagrams](./Murphy_Diagrams.ipynb)\n",
    "- [Flip-Flop Index](./Flip_Flop_Index.ipynb)"
   ]
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    "\n",
    "## Categorical\n",
    "- [FIRM](./FIRM.ipynb)\n",
    "- [Binary Categorical Scores](./Binary_Contingency_Scores.ipynb)\n"
   ]
  },
  {
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    "\n",
    "## Probability\n",
    "\n",
    "- [Brier Score](./Brier_Score.ipynb)\n",
    "- [CRPS for forecasts expressed as CDFs](./CRPS_for_CDFs.ipynb)\n",
    "- [CRPS for ensemble forecasts](./CRPS_for_Ensembles.ipynb)\n",
    "- [Receiver Operating Characteristic (ROC)](./ROC.ipynb)\n"
   ]
  },
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   "source": [
    "\n",
    "## Statistical Tests\n",
    "- [Diebold Mariano](./Diebold_Mariano_Test_Statistic.ipynb)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "002323e9-0e61-449d-a0c5-950948bec4be",
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   "source": [
    "\n",
    "## Processing\n",
    "- [Isotonic Regression and Reliability Diagrams](./Isotonic_Regression_And_Reliability_Diagrams.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "\n",
    "## Other\n",
    "- [Weighting Results](./Weighting_Results.ipynb)\n",
    "- [Angular Data](./Angular_data.ipynb)\n",
    "- [Introduction to Pandas API](./Pandas_API.ipynb)"
   ]
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