Importance of visualization for Statistical Analysis
Learn to create histograms, scatterplots, boxplot, violin plot, bar plot, adding regression line to scatterplot, and matrix of multiple plots
Learn to colour code, modify, adjust axes, add legend boxes for plots
In this project you will learn about several visualization techniques and their importance for Statistical Analysis. The project demonstrates different plotting techniques, for example, histograms, scatter plots, box and whiskers plot, violin plot, bar plot, addition of regression line to scatter plot, and creating matrix of multiple plots. It also discusses the suitability of each plots according to the data type of the variables and illustrates multiple ways to achieve the desired plots efficiently. The project refers to 'Palmer Penguins' data set for the illustrative purpose.
R Programming
Data Visualization (DataViz)
Reporting with graphs
Graph/Plotting Techniques
Exploratory Data Analysis
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction to Visualization for Statistical Analysis
Histogram
Scatterplot
Paired Plot
Box and Whiskers Plot and Violin Plot
Bar Plot
Adding regression line to a plot
Multiple Plots
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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