Udemy – Easy Statistics Data Visualization


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Udemy - Easy Statistics Data Visualization
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 41 lectures (3h 56m) | Size: 936.6 MB
Learn many different Descriptions and graph techniques

What you’ll learn:
Data visualisation
Basic Description types
Intermediate Description types
Advanced Description types
Distribution Descriptions
Relationship Descriptions
Categorical Descriptions
Specialised Descriptions
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, 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 a 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 visualise data is an important aspect in getting data information across to other stakeholders. Many different ways of visualising data have been devised and some are better than other. 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 Descriptions. 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:
To learn and understand the basic methods of data visualization
To learn, in an easy manner, variations and customisations of basic visualization methods
To gain experience of different data visualization techniques and how to apply them
Themes include:
Density Descriptions
Spike Descriptions
Box Descriptions
Violin Descriptions
Stem-and-Leaf Descriptions
Quantile Descriptions
Bar graphs
Pie charts
Dot charts
Radar Descriptions
Scatter Descriptions
Heat Descriptions
Hex Descriptions
Sunflower Descriptions
Lines of best fit
Area Descriptions
Line Descriptions
Range Descriptions
Rainbow Descriptions
Jitter Descriptions
Table Descriptions
Baloon Descriptions
Mosaic Descriptions
and more
Who this course is for
Data analysts
Data scientists
Quantitative students
Quantitative business users