The introduction to moodler is here.
the package moodler is here: moodler.zip
The examples used in the introduction can be sourced into R from examples.R
The following is a list of my R Moodle routines.
DISCLAIMER: These routines were written by me for me, they have not been made user-friendly, don’t have any comments, (some) use a different format and therefore come with no guarantees! If one sounds like you might be able to use them, just create a bunch of problems and check inside of Moodle.
get.moodle.data replaces both getx and getxy
All routines now need a htxt in addition to qtxt and atxt. This is help that will be shown to the students after their first attempt (NOTE not all routines below have been updated)
moodle.table no longer calls r.tbls
getx now works for both numeric and character data without any additional argument
fnumber (five number summary), zscore, emprule, percentages, fivenumber.boxplot, simulation, hp.H0Ha, pvalue, power.mean, power.prop
In most cases the name of the routine pretty much says what it does.
The basic routines to create the newquiz.xml file is
genquiz.R (if fun is already in R)
make.xml.R (if not)
There are a couple of routines that are used by others:
qatxt.R - a general routine use create standard questions and answers.
gen.cont.table.data.R generates data for two categorical variables.
moodle.table.R to display data in quiz.
The routine prints a line with — before the table. This is to get some separation between the values. Unfortunately in htnl5 nice ways to do this with cellpadding etc do not work, and there seems to be no way to include a css style file in Moodle??
anova.tukey.R multiple comparison with Tukey’s method
anova.twoway.R with or without interaction
anova.nonpar.R use Kruskal-Wallis test
anova.transform.R use log transform to get normal residuals
barchart.tshirts.R categorical data problem
basic.R.2.R some basic R questions
basic.R.braquet.R quiz for use of [ , ] notation.
bayes.R questions for my ibayes routine
cat.data.table.R fill in the dable for data from a categorical variable, including percentages and totals.
chi.gof.test.R chi-square goodness of fit test
chi.ind.test.R chi-square test of independence
ci.mean.R find confidence interval for mean. If argument type=1 data is provided, if type=2 summary statistics. If type is missing one is chosen randomly.
ci.prop.R find confidence interval for proportion
ci.sim.R Which of the shown confidence intervals is good?
cont.table.R find percentages and marginals in table
correlation.R estimation, testing or interval estimation for correlation.
correlation.transform.R needs log transform first
emprule.R is the empirical rule working here?
fnumber.R Find five number summary
fivenumber.boxplot.R read five number summary off boxplot
gen.cont.table.data.R generate data for some of the categorical data problems
hp.H0Ha.R choose the right null and alternative hypothesis.
hp.mean.R hypothesis test for mean. If argument type=1 data is provided, if type=2 summary statistics. If type is missing one is chosen randomly.
hp.prop.R hypothesis test for proportion
hp.power.R tests the understaning of the concept of power of a test
hp.sim.R students has to decide in a number of cases whether a test made the right decision or committed an error, type I or II
mean.median.sd.R find mean and/or median and/or standard deviation
meanvsmedian student needs to decide whether to use the mean or the median
normal.check.R does data shown in probability plot come from a normal distribution?
normal.guess.R What are the mean and the standard deviation of this normal curve
outliers.R how many outliers ?
pvalue.R use pvalue app to find pvalue and sample size
percentile.R find percentile of data by hand and with R
power.mean.R what is the power of a certain test for the mean?
power.prop.R what is the power of a certain test for a percentage?
regression.bestmodel.R find best model among standard list
regression.findmodel.R find specific model (quadratic, exponential etc.)
regression.multiple.R various questions in multiple regression problems
regression.simple.R various questions in simple linear regression problems
zscore.R pick which is better based on zscore