Description Usage Format Details References Examples
The data used in simulation 3 of Ramscar et al. (2011) on numerical cognition.
1 |
A data frame with 10 observations on the following 3 variables.
Cues
A character vector specifying cues for quantities, separated by underscores.
Frequency
The frequencies with which the numbers appear in the COCA corpus.
Outcomes
A character vector specifying numerical outcomes associated with the input quantities.
The cues represent learning trials with objects of the same size,
shape and color. The numeric cues represent the presence of at
least one subset of the specified size. The cues exactlyn
represent the presence of exactly n
objects. We are indebted
to Michael Ramscar to making this data set available for inclusion
in the package.
Michael Ramscar, Melody Dye, Hanna Muenke Popick & Fiona O'Donnell-McCarthy (2011), The Right Words or Les Mots Justes? Why Changing the Way We Speak to Children Can Help Them Learn Numbers Faster. Manuscript, Department of Psychology, Stanford University.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | data(numbers)
traceCues=c( "exactly1", "exactly2", "exactly3", "exactly4",
"exactly5", "exactly6", "exactly7", "exactly10", "exactly15")
traceOutcomes=c("1", "2", "3", "4", "5", "6", "7", "10", "15")
ylimit=c(0,1)
par(mfrow=c(3,3),mar=c(4,4,1,1))
for (i in 1:length(traceCues)){
numbers.rw = RescorlaWagner(numbers, nruns=1,
traceCue=traceCues[i],traceOutcome=traceOutcomes[i])
plot(numbers.rw, ylimit=ylimit)
mtext(paste(traceCues[i], " - ", traceOutcomes[i], sep=""),
side=3, line=-1, cex=0.7)
}
par(mfrow=c(1,1))
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