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ScatterExampleImages.Rmd
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```{r ScatterplotDescriptionExamples, name="ScatterExamples", echo=FALSE,fig.width=6, fig.height=6, fig.align="center", out.width='100%',fig.cap="Some example scatterplots"}
par( mfrow = c(2, 3),
omi = c(0, 0, 0, 0) + 0.1) # OUTSIDE margins
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- (2 * x) + 5 + rnorm( length(x), 0, 1)
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
ylim = c(0, 30),
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot A"
)
abline( coef(lm( y ~ x )),
lwd = 2,
col = plot.colour)
text(0, 25,
pos = 4,
"Form: linear\nDirection: positive\nVariation: small")
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- (-2 * x) + 5 + rnorm( length(x), 0, 5) + 25
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
ylim = c(0, 40),
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot B"
)
abline( coef(lm( y ~ x )),
lwd = 2,
col = plot.colour)
text(0, 3,
pos = 4,
"Form: linear\nDirection: negative\nVariation: fairly large")
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- -2 * (x - 4)^2 + 5 + rnorm( length(x), 0, 5) + 80
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
ylim = c(0, 100),
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot C"
)
mod.curve <- lm( y ~ poly(x, 2) )
xnew <- seq(0, 10,
length = 25)
newdata <- data.frame(x = xnew)
ynew <- predict( mod.curve,
newdata = newdata)
lines( ynew ~ xnew,
lwd = 2,
col = plot.colour)
text(0.25, 20,
pos = 4,
"Form: Curved\nDirection: (not relevant)\nVariation: small")
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- 2 * (x - 4)^2 + 5 + rnorm( length(x), 0, 15) + 25
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
ylim = c(0, 145),
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot D"
)
mod.curve <- lm( y ~ poly(x, 2) )
xnew <- seq(0, 10,
length = 25)
newdata <- data.frame(x = xnew)
ynew <- predict( mod.curve,
newdata = newdata)
lines( ynew ~ xnew,
lwd = 2,
col = plot.colour)
text(0, 110,
pos = 4,
"Form: Curved\nDirection: (not relevant)\nVariation: moderate")
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- 2 * (x - 5)^3 + 5 + rnorm( length(x), 0, 15) + 250
y <- y/500
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot E"
)
mod.curve <- lm( y ~ poly(x, 3) )
xnew <- seq(0, 10,
length = 25)
newdata <- data.frame(x = xnew)
ynew <- predict( mod.curve,
newdata = newdata)
lines( ynew ~ xnew,
lwd = 2,
col = plot.colour)
text(0, 0.90,
pos = 4,
"Form: Curved\nDirection: (not relevant)\nVariation: small")
set.seed(2300)
x <- runif(50,
min = 0,
max = 10)
y <- runif(50,
min = 0,
max = 5)
par( mar = c(5, 3.75, 4, 1) + 0.1) # DEFAULT: c(5, 4, 4, 2) + 0.1.
plot( y ~ x,
pch = 19,
las = 1,
ylim = c(0, 6),
xlab = "Explanatory var",
ylab = "Response",
main = "Scatterplot F"
)
mod.curve <- lm( y ~ poly(x, 1) )
xnew <- seq(0, 10,
length = 25)
newdata <- data.frame(x = xnew)
ynew <- predict( mod.curve,
newdata = newdata)
lines( ynew ~ xnew,
lwd = 2,
col = plot.colour)
text(0, 5.75,
"No obvious relationship",
pos = 4)
```