# Problemset Example

Note: Always save your solution files with UTF-8 Encoding!

Example of an RTutor interactive Problemset

Adapt the working directory below and run the setup chunk in RStudio. This creates the problem set files and the sample solution from this solution file. 
#< ignore
```{r "setup"}
library(RTutor)
# Adapt working directory
setwd("D:/libraries/RTutor/RTutor/inst/examples")
ps.name = "Example"; sol.file = paste0(ps.name,"_sol.Rmd")
# character vector of all packages you load in the problem set
libs = c("ggplot2") 
create.ps(sol.file=sol.file, ps.name=ps.name,libs=libs, rps.has.sol=TRUE, addons="quiz")
# Show the problem set in the webbrowser
show.ps(ps.name,sample.solution=FALSE,auto.save.code = TRUE)
```
#>

## Exercise 1 -- Computing with R

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

```{r}
#< task
x = 10:20
# Computing the sum of x
sum(x)
#>
```

Now compute the mean of x.
```{r optional=TRUE}
# Note the chunk option optional = TRUE means
# the user can continue with the next exercise
# without having solved this one

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
```{r}
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.
#>

b) Let `y` be a vector that contains the squared elements of `x`, i.e. for each element $i$ we want $$y_i = x_i^2.$$ Then show `y`.
```{r}
# We should not set this chunk optional
# since we need y in the next chunk
y = x^2
y
```

c) Now use the function `qplot` from the package `ggplot2` to create a scatter plot of `x` against `y`. You can google `r qplot` to get the help for the function `qplot`.

```{r optional=TRUE, dev="svg", fig.width=4}
#< task
library(ggplot2) # load ggplot2 package

# Enter your call to qplot here...
#>
qplot(x,y)
#< test_arg
allow.extra.arg = TRUE 
#>
# The block above allows the user to add extra arguments to the call to qplot, i.e. qplot(x,y,xlab="The variable x"), would also pass the test.
```


#< quiz "prime"
question: What is the 'oddest' prime?
sc:
    - 2*
    - 3
    - 5
    - 7
success: Well, of course the answer is debatable...
failure: Try again.
#>

Note: A quiz as specified below only works in the shiny environment. If you want to design a quiz in an RMarkdown based RTutor problem set, you should use a chunk. E.g. as follows:

Which of the following numbers is the oddest prime? 2,3,5 or 7? Enter you solution in the code below and press "check".

```{r}
2
```
#< award "The oddest prime"
Wouldn't you agree that the only even prime is the odd man out?
#>

## Exercise Submitting your solution

To submit your solution please proceed as follows:

1. Scroll to the top and click on the icon with the bars <i class="fa fa-tasks fa-fw"></i> to see how many points you got so far. If you want to have more points you can try to solve the missing tasks.

2. If you want to submit click on the download button <i class="fa  fa-download fa-fw"></i> at the very right.

3. In the opened tab click the button "Download Submission File". Your browser should then download a file with the extension `.sub`.

4. Upload that downloaded file to your course management system like Moodle, as specified by your instructor.