Humboldt Data Science Statistical Methods and Python tools for Data Analyses

Classes

This section gathers the latest posts.

2016

Class 3 Distributions, mean, evidence and variance.

Lesson about:

  • Distribution (with the toss-a-coin example)
  • Probability Distribution Function (pdf) Gaussian and Poisson
  • Variance, mean and expected Values
  • Python-tip: how to create functions and libraries
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Class 2 Python, Git and basic stats
Live exercices using ipython notebook.

Objectives of the lesson:

  • Learn the basics of python (array, for-loop, masking)
  • Create first function (to be done later): nMAD
  • Do the first plot with matplotlib (scatter, plot, change options)
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Class 1 Introduction
Introduction class

Basic information

In class we defined the basic course information:

  • Time of the class: 13h20 — 14h50
  • Time of the exercises: 12h20 — 13h05

The class will largely make use of Python.

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