Created
November 6, 2020 11:22
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# Why you should plot data before doing statistical tests | |
# CJ Brown 2020-11-06 | |
#More at www.conservationhackers.org | |
library(ggplot2) | |
# | |
# Make some data | |
# | |
n <- 50 #Sample size per group | |
x <- 1:n | |
sd <- 1 #SD for errors | |
y1 <- x - 0.02*x^2-8 + rnorm(n, sd = sd) | |
y2 <- -1*x + 0.02*x^2 +8 + rnorm(n, sd = sd) | |
dat <- data.frame(x = c(x, x), y = c(y1, y2), | |
grp = rep(c("y1", "y2"), each = n)) | |
#Do a t-test first - the wrong way | |
t.test(y1, y2) | |
#shows no 'significant' difference of mean y1 to mean y2 | |
head(dat) | |
#Now plot the data | |
ggplot(dat) + | |
aes(x = x, y = y, color = grp) + | |
geom_point() + | |
stat_smooth() | |
#Clearly y1 and y2 are different | |
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