Explore the basics of data visualization and exploratory data analysis in the [course_title] course.
The course includes three motivating examples and teaches about the ggplot2 which is a data visualisation package for the statistical programming language R, to code. The course illustrates some of the case studies related to world health and economics and infectious disease trends in the United States. The course also discusses how failure to discover problems often leads to flawed analyses and false discoveries.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Course Credit: Harvard University.
|Introduction to Data Visualization||00:05:00|
|Introduction to Distributions||00:02:00|
|Describe Heights to ET||00:02:00|
|Smooth Density Plots||00:07:00|
|Distribution of Female Heights||00:02:00|
|Creating a New Plot||00:02:00|
|Scales, Labels, and Colors||00:02:00|
|The Dot Placeholder||00:02:00|
|Sorting Data Tables||00:02:00|
|Case Study: Trends in World Health and Economics||00:02:00|
|Life Expectancy and Fertility Rates||00:02:00|
|Time Series Plots||00:05:00|
|Stratify and Boxplot||00:07:00|
|Introduction to Data Visualization Principles||00:02:00|
|Encoding Data Using Visual Cues||00:02:00|
|Know When to Include Zero||00:03:00|
|Do Not Distort Quantities||00:02:00|
|Order by a Meaningful Value||00:02:00|
|Show the Data||00:03:00|
|Ease Comparisons: Use Common Axes||00:03:00|
|Ease Comparisons: Compared Visual Cues Should Be Adjacent||00:02:00|
|Encoding a Third Variable||00:01:00|
|Case Study: Vaccine||00:02:00|
|Avoid Pseudo and Gratuitous 3D Plots||00:02:00|
|Avoid Too Many Significant Digits||00:02:00|
|Submit Your Assignment||00:00:00|
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