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statistical-graphics

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In this course, you will learn how to use Seaborn, a Python library for producing statistical graphics. You will learn how to use Seaborn's sophisticated visualization tools to analyze your data, create informative visualizations, and communicate your results with ease.

  • Updated Sep 26, 2025

Supplementary materials for the following publication: Davydenko, A., & Goodwin, P. (2021). Assessing point forecast bias across multiple time series: Measures and visual tools. International Journal of Statistics and Probability, 10(5), 46-69. https://doi.org/10.5539/ijsp.v10n5p46

  • Updated Oct 4, 2021
  • R

This comprehensive course covers the fundamental concepts and practical techniques of Matplotlib, the essential plotting library in Python. Learn to create various types of charts and visualizations including line plots, bar charts, scatter plots, histograms, pie charts, and subplots.

  • Updated Sep 26, 2025

Performed exploratory data analysis (EDA) in python on the world happiness report datasets (for years 2015, 2016, 2017, 2018, and 2019) from Kaggle; to analyze how measurements of well-being can effectively help assess the progress of nations across the world.

  • Updated Jan 19, 2022
  • Python

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