In skranz/RTutorExample: RTutor problem set example for a package.

Problemset Example

Example of an RTutor interactive Problemset

Author: Sebastian Kranz

Adapt the working directory below and press Ctrl-Alt-R (run all chunks). This creates the problem set files and the sample solution from this solution file.

< ignore

library(restorepoint)
# facilitates error detection
set.restore.point.options(display.restore.point=!TRUE)

library(RTutor)
#library(restorepoint)
setwd("D:/libraries/RTutor/examples")
ps.name = "Example"; sol.file = paste0(ps.name,"_sol.Rmd")
libs = c() # character vector of all packages you load in the problem set
#name.rmd.chunks(sol.file) # set auto chunk names in this file

create.ps(sol.file=sol.file, ps.name=ps.name, user.name=NULL,libs=libs, stop.when.finished=FALSE)

show.ps(ps.name, user.name="Seb", load.sav=!TRUE,  sample.solution=FALSE, run.solved=!TRUE, catch.errors=TRUE, launch.browser=!TRUE, make.session.ps=TRUE)

stop.without.error()

>

Exercise 1 -- Summary statistics

a) First part

Compute 1+1+1 and store it in z

#< compute z

## First store the intermediate result 1+1 in a variable 'y'
y = 1+1

## Now compute z by adding 1 to y
z = y+1
#>

b) We often want to compute some summary statistic of a vector. For example:

#< task
x = 10:20
# Computing the sum of x
sum(x)
#>

Now compute the mean of x.

mean(x)
#< hint
cat("There already exist R functions for many things. To find them use Google, e.g. search for 'R compute mean'.")
#>

< info "useful functions for numeric vectors"

Here are examples for useful R functions

max(c(1,5,2)) # returns maximum
min(c(1,5,2)) # returns minimum

sum(c(1,5,2,NA), na.rm=TRUE) # returns sum of all numbers, ignore NA
cumsum(c(1,5,2)) # returns cummulated sum
diff(c(1,5,2)) # returns the vector of differences

>

< award "mean means mean"

Well, in some occasions one can just guess the name of an R function. The function to compute the mean of a vector, or matrix is called 'mean'. Usually, it is much quicker to goggle than to guess function names, however.

>

Exercise 2 -- Computing with vectors

#< settings
import.var = c("x")
#>

a) Let y be a vector that contains the squared elements of x. Show y

y = x^2
y

b) Run this chunk and check out the data button

#< task_notest
# Generating a data frame
df = data.frame(a=c(1,1,2,2,2,3,3,4), b = runif(8), c="Hi")
df
#>

That's all folks!

skranz/RTutorExample documentation built on May 30, 2019, 2:02 a.m.