In CIP-RIU/hidap: High Interactive Data Analysis Platform for Plant breeding

# Some parameters
p1 <- length(params$x)
p2 <- max(table(params$x))
p3 <- length(table(params$x))

It looks like you have a numeric trait. You can see a descriptive summary below:

output <- summary(params$x)
output

sk <- 3 * (mean(params$x) - median(params$x)) / sd(params$x)

r if (sk > 0.5) {"It looks like you have some positive skewness because your mean is quite larger than your median. Watch out with this if you want to fit a model that assumes normality." }

r if (sk < -0.5) {"It looks like you have some negative skewness because your mean is quite smaller than your median. Watch out with this if you want to fit a model that assumes normality." }

r if (p1 > 25 & (p1 / p3 <= 2 | (p1 / p3 > 2 & p3 > 20))) {"A boxplot could be a suitable plot for these data:"}

if (p1 > 25 & (p1 / p3 <= 2 | (p1 / p3 > 2 & p3 > 20)))
  boxplot(params$x)

r if (p1 > 25 & p1 / p3 > 2 & p3 <= 20) {"For this trait a frequency table could produce a good display of the data:"}

if (p1 > 25 & p1 / p3 > 2 & p3 <= 20)
  table(params$x)

r if(p1 <= 25) {"A dotplot could be a suitable plot for these data:"}

if (p1 <= 25)
  stripchart(params$x)

r if (p1 > 25 & p1 / p3 < 2 & p2 / p1 > 0.05) {"Although your trait seems to be on a continuous scale, there are some values with a very high frequency. What out with this if you plan to fit a model that assumes normality. You can see these values and their frequency below:"}

if (p1 > 25 & p1 / p3 < 2 & p2 / p1 > 0.05)
  table(params$x)[table(params$x) / p1 > 0.05]

CIP-RIU/hidap documentation built on April 30, 2021, 9:21 p.m.