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Easy Statistics: Data Visualization

Easy Statistics: Data Visualization Learn many different plots and graph techniques
Easy Statistics: Data Visualization Learn many different plots and graph techniques

Easy Statistics: Data Visualization

Learn many different plots and graph techniques

What you’ll learn

Easy Statistics: Data Visualization

  • Data visualization
  • Basic plot types
  • Intermediate plot types
  • Advanced plot types
  • Distribution plots
  • Relationship plots
  • Categorical plots
  • Specialized plots

Requirements

  • None

Description

Make sure to check out my Twitter feed for promo codes and other updates (easystats3)

Learning and applying new statistical techniques can often be a daunting experience.

“Easy Statistics” is designed to provide you with a compact, and easy to understand, a course that focuses on the basic principles of statistical methodology.

This course will teach you the many different methods to visualize data

Visualizing and graphing data is vital in modern data analytics. Whether you are a data scientist, student of quantitative methods, or a business user, having an understanding of how to visualize data is an important aspect of getting data information across to other stakeholders. Many different ways of visualizing data have been devised and some are better than others. However, each method has advantages and disadvantages, and having a solid understanding of what visualization might be best suited is key to delivering a concise and sharp “data message”.

Often, it takes years of experience to accumulate knowledge of the different graphs and plots. In these videos, I will outline some of the most important data visualization methods and explain, without any equations or complex statistics, what are the advantages and disadvantages of each technique.

The main learning outcomes are:

  1. To learn and understand the basic methods of data visualization
  2. Learn, in an easy manner, variations and customizations of basic visualization methods
  3. To gain experience in different data visualization techniques and how to apply them

Themes include:

  • Histograms
  • Density plots
  • Spike plots
  • Rootograms
  • Box plots
  • Violin plots
  • Stem-and-Leaf plots
  • Quantile plots
  • Bar graphs
  • Pie charts
  • Dot charts
  • Radar plots
  • Scatter plots
  • Heat plots
  • Hex plots
  • Sunflower plots
  • Lines of best fit
  • Area plots
  • Line plots
  • Range plots
  • Rainbow plots
  • Jitter plots
  • Table plots
  • Baloon plots
  • Mosaic plots
  • and more

Who this course is for:

  • Data analysts
  • Data scientists
  • Quantitative students
  • Quantitative business users
  • Last updated 8/2021

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