A webR tutorial
The Comeback Kids β Part I
Import the data
Before we begin, please press Run Code on the code chunk below to import the data.
The scenario
You are teaching an undergraduate applied statistics course with 500 students. After giving the midterm exam, you find a wide distribution of scores. In the code chunk below, create a histogram of the midterm scores (the data frame is called exams and the midterm scores are stored in a variable called midterm).
The intervention
The average score is lower than youβd hoped. You are particularly concerned about the students who performed poorly, so you decide to launch a special effort to help them improve. You select the 25 lowest performers and invite them to participate in a weekly tutoring session with you. Over the next six weeks, you focus on helping these students improve.
The outcome
At the end of the semester, you give the final exam.
In the code chunk below, first create a new variable called diff in which you subtract the midterm score from the final score. Then, filter the data frame to pull out the 25 poorest performers from midterm (these are the students you helped). You can use the slice_min() function to select the bottom 25 students for the midterm. The function selects the rows with the smallest values of a given column. The arguments are order_by
(the column by which to find the smallest values β that is midterm in our example), and n
(the number of rows to return β that is 25 in our example). Inspect the lowest midterm performerβs midterm, final and difference score. Jot down your thoughts.
Here they are in an easier to read format:
Now, please calculate the average improvement for these 25 students.
You are excited to see that the 25 students that you tutored improved so much! You are curious to compare that improvement to the other 475 students that you didnβt tutor. Please calculate the average improvement for those students in the code chunk below.
Take a few moments to discuss what you have observed with your partner. Jot down your thoughts.