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Data Science Visualization - Module 2

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Course Description

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  1. 1

    Data Types

    In this course we introduce you to the basics of various data types.
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  2. 2

    Quantiles, Percentiles, and Boxplots

    Quantile-Quantile Plots, Percentiles, Boxplots, Distribution of Female Heights
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  3. 3


    An overview of distributions and their characteristics
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  4. 4

    Normal Distributions

    In this chapter we go over the normal distribution.
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  5. 5

    Robust Summaries with Outliers

    dplyr, The Dot Placeholder, Group By, Sorting Data Tables
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  6. 6

    Introduction to ggplot2

    You'll learn how to make use of the powerful R package, ggplot2, for visualization
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  7. 7

    Summarizing with dplyr

    We will practice our dplyr skills by will be working with data from the survey collected by the United States National Center for Health Statistics (NCHS)
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  8. 8

    Exploring the gapminder dataset

    Visualizing gapminder results with dplyr and ggplot
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  9. 9

    Data Visualization Principles - Part 1

    Show the Data, Ease Comparisons - Use Common Axes, Consider Transformations, Ease Comparisons - Compared Visual Cues Should Be Adjacent
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  10. 10

    Data Visualization Principles - Part 2

    Part 2 of data visualization principles exercises
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  11. 11

    Data Visualization Principles - Part 3

    Part 3 of data visualization principles exercises
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