Commit ef7ee659 authored by Simon Pintarelli's avatar Simon Pintarelli

update readme

parent 30b12405
This is intended as a user-friendly (and easy to customize) alternative to the previous exam statistic script
written in perl.
This is intended as a user-friendly (and easy to customize) alternative to the previous exam statistics script.
.. role:: bash(code)
:language: bash
......@@ -8,10 +7,10 @@ written in perl.
Installation
============
Run :bash:`./install.sh`. Be patient, if you run this on a D-MATH computer it will
take >5min.
Run :bash:`./install.sh`. This will download and compile the required R-packages and install
pandas and xlwt for python 3.
Of course you have to clone or download the git repo first:
You have to clone or download the git repo first:
.. code:: shell
......@@ -35,11 +34,12 @@ Usage
3. Open ``marks.xls`` in a spreadsheet editor (for example localc) and enter
the number of points per task for each student (Columns A1..An). Add or remove
columns for tasks as needed. Save as Excel document to ``marks.xls``.
4. Open the file ``statistics.Rnw`` in a text editor and fill the data in the block called "User
Settings".
4. Open the file ``statistics.Rnw`` in a text editor and fill in the variables in the
block "User Settings". That means the lecture title, the interpolation points for
the grading scale and the maximal number of points per task.
5. Open a shell and type :bash:`./2-generate-stats-and-edoz-upload`. This will generate the
files ``statistics.pdf`` and ``edoz-final.txt``
6. Check the grades of a few students manually to make sure that results in
6. Check the grades of a few students manually to make sure that the results in
``edoz-final.txt`` are correct.
7. Upload ``edoz-final.txt`` to edoz by clicking on ``Import Data``.
......@@ -52,7 +52,7 @@ Preview
Links
=====
If you'd like to customize the script have a look at the following packages and the file ``statistics.Rnw``.
If you'd like to customize the script, have a look at the following packages and the file ``statistics.Rnw``.
- Manipulate data in R: `dplyr <https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html>`_
- Plots in R `ggplot2 <http://www.cookbook-r.com/Graphs/>`_
......
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