The folder Lab11Data contains several CSV data files. dfiles <- dir("Lab11Data", full.names=TRUE) dfiles ## [1] "Lab11Da

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The Folder Lab11data Contains Several Csv Data Files Dfiles Dir Lab11data Full Names True Dfiles 1 Lab11da 1 (156.74 KiB) Viewed 56 times

The folder Lab11Data contains several CSV data files. dfiles <- dir("Lab11Data", full.names=TRUE) dfiles ## [1] "Lab11Data/study1.csv" "Lab11Data/study2.csv" "Lab11Data/study3.csv" ## [4] "Lab11Data/study4.csv" "Lab11Data/study5.csv" "Lab11Data/study6.csv" ## [7] "Lab11Data/study.csv" "Lab11Data/study8.csv" "Lab11Data/study9.csv" 1. Write R code to read in the first file. Print the tibble that you just read in. Use names() to change the column names of the tibble to x and y. Repeat for the second file. How many observations are in these first two files? 2. Use vector() to create an empty vector called ff that is of mode "list" and length 9. Now write a for() loop to loop over the 9 files in dfiles and for each (i) read the file in to a tibble, and change the column names to x and y as in part (1), and (ii) copy the tibble to an element of your list ff. 3. Write a function called read.study_data that takes a vector of data file names (like dfiles) as input, reads the data files into a list, assigns class "study_data" to the list, and returns the list. Your function should use length(dfiles) to determine the number of files. 4. Write a function plot.study_data() that takes an object of class "study_data" as input. The first 5 lines of your function should be the following, which creates a tibble with columns study, x and y: dat <- NULL for(i in seq_along (ff)) { d <- ff [] dat <- rbind (dat, tibble(study=i,x=d$x, y=d$y)) } Have your function coerce study to a factor, and then call ggplot() to make a plot of y versus x, with different colours for the different studies. Add points and smoothers to your plot.