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Distributions of One Variable

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An Introduction to Statistics with Python

Part of the book series: Statistics and Computing ((SCO))

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Abstract

This chapter shows how to characterize the position and the variability of a distribution, and then uses the normal distribution to describe the most important Python methods common to all distribution functions. Then the most important discrete and continuous distributions are presented, such as the t-distribution, chi-square-distribution, and the F-distribution.

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Notes

  1. 1.

    https://github.com/thomas-haslwanter/statsintro_python/tree/master/ISP/Code_Quantlets/06_Dist ributions/binomialTest.

  2. 2.

    https://github.com/thomas-haslwanter/statsintro_python/tree/master/ISP/Code_Quantlets/06_Dist ributions/distDiscrete.

  3. 3.

    https://github.com/thomas-haslwanter/statsintro_python/tree/master/ISP/Code_Quantlets/06_Dist ributions/distNormal.

  4. 4.

    https://github.com/thomas-haslwanter/statsintro_python/tree/master/ISP/Code_Quantlets/06_Dist ributions/centralLimitTheorem.

  5. 5.

    https://github.com/thomas-haslwanter/statsintro_python/tree/master/ISP/Code_Quantlets/06_Dist ributions/distContinuous.

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© 2016 Springer International Publishing Switzerland

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Haslwanter, T. (2016). Distributions of One Variable. In: An Introduction to Statistics with Python. Statistics and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-28316-6_6

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