Task 1.
Use the code dplyr::glimpse() to obtain information about your data set.
a. Explain the information obtained with that code.
Task 2
Using the codes nrow() and ncol(), create objects to save the number of columns (variables) and number of rows (observations) your data set contains.
Using Inline R codes, present these values.
Make sure to use two back quotes to ensure that your values are highlighted on your report. e.g., ``r variables``
Note: this is the back quote key:
Task 3
Using the code names(), make a list of all variables in the data set, and present it as a data frame.
Task 4
Present the number of categories contained in variable wine type.
For this, use the code table() as explained in class, but do not present the table (save the table with an object name).
Use the table to present the categories of wine type using a bar plot. Provide different colors to each bar.
Use code text(), as indicated in my website, to add the frequencies on top of each bar. Explain the codes you used and the data you obtained on your graph.
Task 5.
For each category of wine type, ask a simple question:
What is the mean color intensity per wine type?
To answer that question, create an object named mean_color (or any other name of your preference) and use the tapply() code to answer that question. This code allows you to apply a function, like mean, median, to subsets of a variable. (https://youtu.be/9ZWHfozPn6k)
Remember to add the numerical Variable name first, then the categorical Variable name, and finally indicate the function(mean, sum, sd).
Do not present the outcome of the tapply() code, using the object you created, present the values in a carplot().
Using color = , add different colors to each category. Using code text(), add the mean values to each variable.
Since this is the first time you will do this, I will help you. See tapply() at the end of this document.
Task 6.
Similar to task 5, and using the tapply() code, create four objects to store the following data:
• The mean phenols per wine type.
• The standard deviation of phenols per wine type.
• The median phenols per wine type.
• The variance of phenols per wine type.
Observe the file “Vectors and Matrices R” in canvas, use it as a guide to present all the values using a table (first create a matrix, add column names, row names, then present the matrix).
Clue: Create three vectors: vector 1 contains the names of all four objects, vector 2 contains the names for the columns (wine types), and vector 3 contains the names of statistics (mean, sd, median, variance).
Create a matrix using vector 1.
Use vector 2 to add column names using code colnames(). Use vector 3 to add row names using code rownames().
All these codes and their use are explained in the R file mentioned above.
Provide the Matrix with a name and be sure to present only the final product on your report.
Task 7
Now you want to know the frequency distribution of each continuous variable per wine type. For example: what is the distribution of sepal width per species in the data set iris?
One way to accomplish this task it by using histograms. In the x-axis you observe the sepal width distribution presented as bins, and in the y-axis you observe the frequency of observations per bin. I will help you with these codes
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