How do I calculate the number of dots that lie above and below the regression line on a scatter plot?
data = read.csv("info.csv")
par(pty = "s")
plot(data$col1, data$col2, xlab = "xaxis", ylab = "yaxis", xlim = c(0,
1), cex.lab = 1.5, cex.axis = 1.5, ylim = c(0, 1), col.lab = "red",
col = "blue", pch = 19)
abline(a = -1.21, b = 2.21)
x <- 1:10
set.seed(1)
y <- 2*x+rnorm(10)
plot(y~x)
fit <- lm(y~x)
abline(fit)
resi <- resid(fit)
#below the fit:
sum(resi < 0)
#above the fit:
sum(resi > 0)
Edit: If you did (for some unknown reason) something like this:
x <- 1:10
set.seed(1)
y <- 2*x+rnorm(10)
plot(y~x)
abline(-0.17,2.05)
You can do this:
yfit <- 2.05 * x - 0.17
resi <- y - yfit
sum(resi < 0)
sum(resi > 0)
If I've read the question properly, the answer would be.
Using the above should be sufficient to find the numbers (counts) you are after.
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