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  3. Data Science Visualization - Module 2
  • 1

    Data Types

    Free

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

  • 2

    Quantiles, Percentiles, and Boxplots

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

  • 3

    Distributions

    An overview of distributions and their characteristics

  • 4

    Normal Distributions

    In this chapter we go over the normal distribution.

  • 5

    Robust Summaries with Outliers

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

  • 6

    Introduction to ggplot2

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

  • 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)

  • 8

    Exploring the gapminder dataset

    Visualizing gapminder results with dplyr and ggplot

  • 9

    Data Visualization Principles - Part 1

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

  • 1

    Data Visualization Principles - Part 2

    Part 2 of data visualization principles exercises

  • 1

    Data Visualization Principles - Part 3

    Part 3 of data visualization principles exercises

Initializing

Exercise

Exercise 15. Histograms

We are going to shift our focus from the murders dataset to explore the heights dataset.

We use the geom_histogram function to make a histogram of the heights in the heights data frame. When reading the documentation for this function we see that it requires just one mapping, the values to be used for the histogram.

What is the variable containing the heights in inches in the heights data frame?

Instructions

50 XP

Possible answers