Pen & Paper


Blogging with R

16 May 2013

I used knitr, shiny server and R markdown to build my research artefact, a cloud-based note-taking application. Now that the disseration is out of the way, I’m able to focus on completing the developement of my note-taking application in the coming months.

yihui has a few words of wisdom to all “brave professors” - students should be submitting their papers or assignments in R + knitr instead of boring Word documents. So true! Yes, R + knitr is exciting, fast and flexible. Everything I’m doing in this blog post is done in simple text, including the elegant Scatterplot Matrix below:

Scatterplot Matrix

The matrix summaries the assoication observed among the test variables, ie, number of words recorded in lecture notes (Word), number of keyword captured (Keyword) and quiz results (Score).

plot of chunk scatterplot

One of the most interesting findings in my study was that the number of words recorded in lecture notes was negatively correlated with the test scores in the “Pen and Paper” group but the pair of variables had a positive correlation in the “Computer Application” group. Technology has completely reversed the relationship between “number of words in lecture notes” and “test scores”. Below is the correlation matrix with P-value (again, all done in text with exactly two lines of codes):

Correlation Matrix & P-values

# P-value - Pen and Paper
rcorr(as.matrix(nt.000))
##          Word Keyword Score
## Word     1.00    0.25 -0.60
## Keyword  0.25    1.00  0.13
## Score   -0.60    0.13  1.00
## 
## n= 9 
## 
## 
## P
##         Word   Keyword Score 
## Word           0.5176  0.0854
## Keyword 0.5176         0.7311
## Score   0.0854 0.7311
# P-value - Computer App
rcorr(as.matrix(nt.111))
##         Word Keyword Score
## Word    1.00    0.54  0.55
## Keyword 0.54    1.00  0.50
## Score   0.55    0.50  1.00
## 
## n= 14 
## 
## 
## P
##         Word   Keyword Score 
## Word           0.0486  0.0415
## Keyword 0.0486         0.0676
## Score   0.0415 0.0676