Description Usage Arguments Value Author(s) See Also Examples
This function calculates a Net Promoter Score from a vector of
Recommend scores, ideally numeric
ones. An attempt will
be made to coerce factor
, or character
data.
NA
values, either in the data, or generated by type coercion, are
automatically omitted from the calculation. No warning is given in the former
case. Net Promoter Scores generated are on a [-1,1] scale; you may want to
multiply them by 100 (and perhaps round them!) prior to presentation.
1 2 3 |
x |
A vector of Recommend scores |
breaks |
A |
na.rm |
a logical value indicating whether |
a Net Promoter Score.
Brendan Rocks foss@brendanrocks.com
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # This will generate 1000 dummy Likelihood to Recommend reponses
x <- sample(
0:10, 1000, replace = TRUE,
prob = c(0.02, 0.01, 0.01, 0.01, 0.01, 0.03, 0.03, 0.09, 0.22, 0.22, 0.35)
)
# Here are the proportions of respondents giving each Likelihood to
# Recommend response
prop.table(table(x))
# Here's a histrogram of the scores
hist(
x, breaks = -1:10,
col = c(rep("red", 7), rep("yellow", 2), rep("green", 2))
)
# Here's a barplot. It's very similar, though for categorical responses
# it's often slightly easier to interpret.
barplot(
prop.table(table(x)),
col = c(rep("red", 7), rep("yellow", 2), rep("green", 2))
)
# Here's the NPS
nps(x)
# You can round it if you like
round(nps(x)) ; round(nps(x), 1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.