Equal Variance Testing - Two Groups
Trout.250 <- c(508, 479, 545, 531, 559, 422, 547, 525, 420, 491, 508, 511, 569, 453,
533, 460, 523, 540, 463, 502)
Trout.300 <- c(461, 464, 344, 559, 445, 617, 402, 531, 535, 413, 456, 479, 393, 504,
416, 468, 368, 519, 523, 531)
Farmed.Trout <- data.frame(cbind(Trout.250, Trout.300))
str(Farmed.Trout)
'data.frame': 20 obs. of 2 variables:
$ Trout.250: num 508 479 545 531 559 422 547 525 420 491 ...
$ Trout.300: num 461 464 344 559 445 617 402 531 535 413 ...
summary(Farmed.Trout)
Trout.250 Trout.300
Min. :420.0 Min. :344.0
1st Qu.:475.0 1st Qu.:415.2
Median :509.5 Median :466.0
Mean :504.4 Mean :471.4
3rd Qu.:534.8 3rd Qu.:525.0
Max. :569.0 Max. :617.0
with(Farmed.Trout,boxplot(Trout.250,Trout.300,
col= "lightgray",
main= "Weights of Aquaculture Raised Rainbow Trout",
xlab= "Pen density (No. fish)",
ylab= "Weight (g)",
ylim= c(300,650),
names= c("250 per pen","300 per pen"), # group names
las= 1,
boxwex =0.6))
with(Farmed.Trout, var.test(Trout.250, Trout.300))
F test to compare two variances
data: Trout.250 and Trout.300
F = 0.38583, num df = 19, denom df = 19, p-value = 0.04421
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.1527172 0.9747866
sample estimates:
ratio of variances
0.3858324