Statistical Analysis with Matplotlib
This course demonstrates how Python and Matplotlib are used to work on different statistical distributions. Standard charts like histograms, boxplots, and violinplots are used to display statistical distributions.
The package Matplotlib in Python is a popular package for data visualization. In this course, Statistical Analysis with Matplotlib, you’ll learn how to use this package to demonstrate the concept of statistical distributions. First, you’ll learn about probabilities within the values of a variable and how to identify the underlying statistical distribution. Next, you’ll discover the theoretical background of statistical distributions, and how to generate a desired distribution with a random number generator. Finally, you’ll understand what the general implications of the findings are. When you’re finished with this course, you’ll have the skills and knowledge of visually identifying a distribution and how to generate pre-defined distributions.
Author Name: Martin Burger
Author Description:
Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.
Table of Contents
- Course Overview
1min - Exploring Variable Distributions with Plots
23mins - Using Different Chart Types for Distributions
27mins
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