.. note::
    :class: sphx-glr-download-link-note

    Click :ref:`here <sphx_glr_download_intro_scipy_auto_examples_plot_t_test.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_intro_scipy_auto_examples_plot_t_test.py:


==========================================
Comparing 2 sets of samples from Gaussians
==========================================





.. image:: /intro/scipy/auto_examples/images/sphx_glr_plot_t_test_001.png
    :class: sphx-glr-single-img





.. code-block:: python


    import numpy as np
    from matplotlib import pyplot as plt

    # Generates 2 sets of observations
    samples1 = np.random.normal(0, size=1000)
    samples2 = np.random.normal(1, size=1000)

    # Compute a histogram of the sample
    bins = np.linspace(-4, 4, 30)
    histogram1, bins = np.histogram(samples1, bins=bins, density=True)
    histogram2, bins = np.histogram(samples2, bins=bins, density=True)

    plt.figure(figsize=(6, 4))
    plt.hist(samples1, bins=bins, density=True, label="Samples 1")
    plt.hist(samples2, bins=bins, density=True, label="Samples 2")
    plt.legend(loc='best')
    plt.show()



**Total running time of the script:** ( 0 minutes  0.042 seconds)


.. _sphx_glr_download_intro_scipy_auto_examples_plot_t_test.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_t_test.py <plot_t_test.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_t_test.ipynb <plot_t_test.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_