In this exercise, you will be using a dataset called Iris that is built into R. R has several datasets available, but the Iris dataset is a very popular and can be used for several data exploration scenarios.

In this exercise, you will be using a dataset called Iris that is built into R. R has several datasets available, but the Iris dataset is a very popular and can be used for several data exploration scenarios.

To load the iris dataset into R, you will want to write the following command:

library(datasets)
data(iris)

1. Create a new R markdown document.
2. Add a title to the document, along with your name.
3. Add a level 1 header that provides a name for the iris analysis.
4. Add a code chunk that assigns the iris dataset to a new variable (iris is included in the R environment). Make sure this code chunk is visible in the document.
5. Add a level 2 header that states ‘Average Sepal Length by Species’
6. Using dplyr, group the dataset by species, and provide the average sepal length. Include the code and the results in the document.
7. Add a code chunk that calls ggplot2 library, but do not include it in your presentation.
8. Add a level 2 header that states ‘Visualizations’
9. Using a combination of histograms and box plots, visualize the differences in sepal length, sepal width, petal length, and petal width between the species. Set your code to be displayed in the document.
10. Under the visualizations, write a brief paragraph describing the differences between the species.

Submission Instructions

For all assignments in this course, you must export the script or Markdown file to PDF. All submissions must include a PDF that includes your code and output. You are welcome to include your script or a link to GitHub or another external repo, but you must also include a PDF at a minimum. No zip files are accepted either.

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