GV900 : Political Explanation - Write an R Code File - Computer Science Assignment Help

Assignment Task :

Write an R code file named (gv900-HW1.R) to complete the following tasks. The easiest way to write an R code file is to start with an existing file: Duplicate an existing R code file that you have (e.g., gv900-week4-JointExercise.R) and modify the file contents accordingly. 

Rules 

• Submit two files, and two files only. That is, submit (1) the coversheet (ESSAY COVERSHEET 2020-2021.docx, available on Moodle) and (2) your R code file (gv900-HW1.R). Don’t submit your graph or other outputs. You’ll earn 5 points if you do all of these correctly. 

• Make sure that you delete your name from your R code file. You’ll earn 5 points if you do this correctly. 

• Execute everything before you submit (e.g., CTRL + A & CTRL + Return on a Windows PC; Command + A & Command + Enter on a Mac machine), and make sure your file runs without an error. I will execute your file to check if you did it. You’ll earn 5 points if your R file runs without an error. 

• Your file must have a proper header. You’ll earn 5 points if you do this correctly. 

• Add comments and annotations to everything you do. Try to make your code file look like my code file. If your code file doesn’t have a proper annotation, you’ll lose 5 points. Don’t copy and paste all the questions into your R code file, but do show me the question number for each question. You’ll earn 5 points if you do this correctly. 

Tasks 

1. Load the “world” dataset (world.csv), and store it as an object named world.data. 

2. The data set contains a dummy variable (i.e., a nominal variable with two categories) named oecd that classifies countries into two groups, OECD member countries and non member countries. One way to describe and summarize the information contained in a nominal variable is to describe the distribution numerically. As we learned during the past weeks, we describe the distribution of a nominal variable numerically by creating a frequency table. Create a frequency table of this variable and store it into a data frame object ft.oecd. The table has to have three columns: values (initially called “Var1”), frequency (called “Freq”), and percentage (should be called “Percentage”). Change the column name of the first column to “OECD Member?”. 

3. According to the frequency table you created above, (A) how many countries in the data set are OECD members? (B) How many countries in the data set are not? (C) What percentage of countries are OECD members? (D) What percentage of countries are non members? Give me four answers (four numbers) as a comment. Note: for this task, you don’t need an R command. Just read the table and tell me the numbers. Don’t forget to comment them out

4. Another way to describe and summarize a nominal variable is to draw a frequency distri bution graph. For nominal variables, we draw a bar chart. Using the functions available in the ggplot2 package (e.g., geom bar), draw a bar chart of the dummy variable that measures OECD membership. 

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