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ECON3740 INTRODUCTORY ECONOMETRICS
1: Basics of R Studio DUE DATE: September 24 2021 Note on what to submit In some cases I will ask you to submit your program, sometimes the output, and sometimes plots or histograms. What I don’t want you to submit is the contents of the Console window. Suppose the question is as follows: Find the data file called forest.csv and write an R program to read it in, compute and write the mean rate of deforestation to a text file, and generate a plot showing deforestation against population density. Submit your program, your output file and your plot. What I am looking for is the following: Program: # REMOVE ALL OBJECTS IN MEMORY rm(list=ls(all=TRUE)) # READ IN DATA data=read.csv(file="forest.csv", header=TRUE) # REPORT MEAN POP DENSITY sink("popden.txt") cat("The mean population density is ", mean(data$Pop.den..people.per.000.ha..),"\n") sink() # PLOT DEFORESTAION vs POP DENSITY plot(data$Deforest....forest.lost.per.year. ~ data$Pop.den..people.per.000.ha.., xlab="Population Density", ylab="Deforestation", pch=16) popden.txt file: The mean population density is 639.427 Plot: 2 What I am not looking for is the content of the console window in R studio (bottom left): 3 That part of the screen is your workspace. But don’t copy and paste what’s in it if I have asked for a program file or an output file. The reason is that part of the skill of programming is being able not only to do calculations, but to go back later and re-do the exact same calculations and make sure the answers are preserved somewhere. To do that you need to have a working program in a saved file which writes the important results to an external file you can also save. The console window shows what’s going on during your session but it’s not a saved input or output file. 1. [10] Find the ORANGE.XLS data set and re-save it as a CSV file. Write an R program to a. read the CSV data set, b. make a scatter plot of the price of regular oranges (y axis) against the price of organic oranges (x axis). Make the graph presentable by putting informative labels on the axes and giving it a title. c. plot a histogram of the prices of organic oranges using the col=”gray” option. Submit your R program and the two graphs. 2. [10] Use the dataset EDUC.XLS from the Koop archive and convert it to a CSV file. It contains data on expenditure on education (EDUC), GDP and Population for 38 countries around the world. Write an R program to read the data, make an X-Y scatter plot showing Education spending versus Population and then compute and write to an output file a. the correlation between Education spending and GDP as a sentence “The correlation between education spending and GDP is x”. b. the covariance between GDP and Population as a sentence “The covariance between GDP and population is x” Submit your R program, the output file and the graph. 3. [20] Obtain the file HPRICE.XLS and convert it to a CSV file. Write an R program that reads the data, then writes the following to an output file: a. the mean of house prices compared to the mean after trimming 5% from each end of the sample b. the mean of the lot size of the first 20 observations in the sample c. the correlation between house price and lot size (make sure to verify that the answer matches the one on page 18 of the textbook) Submit your R program and the output file.