Module # 10 Introduction to ANOVA

> HighStress<- c(10,9,8,9,10,8)
> ModerateStress<- c(8,10,6,7,8,8)
> LowStress<- c(4,6,6,4,2,2)
> Combined_Groups<- data.frame(cbind(HighStress, ModerateStress, LowStress))
>
> HighStress
[1] 10 9 8 9 10 8
> ModerateStress
[1] 8 10 6 7 8 8
> LowStress
[1] 4 6 6 4 2 2
> Combined_Groups
HighStress ModerateStress LowStress
1 10 8 4
2 9 10 6
3 8 6 6
4 9 7 4
5 10 8 2
6 8 8 2
> summary(Combined_Groups)
HighStress ModerateStress LowStress
Min. : 8.00 Min. : 6.000 Min. :2.0
1st Qu.: 8.25 1st Qu.: 7.250 1st Qu.:2.5
Median : 9.00 Median : 8.000 Median :4.0
Mean : 9.00 Mean : 7.833 Mean :4.0
3rd Qu.: 9.75 3rd Qu.: 8.000 3rd Qu.:5.5
Max. :10.00 Max. :10.000 Max. :6.0
>
> Stacked_Groups<- stack(Combined_Groups)
> Stacked_Groups
values ind
1 10 HighStress
2 9 HighStress
3 8 HighStress
4 9 HighStress
5 10 HighStress
6 8 HighStress
7 8 ModerateStress
8 10 ModerateStress
9 6 ModerateStress
10 7 ModerateStress
11 8 ModerateStress
12 8 ModerateStress
13 4 LowStress
14 6 LowStress
15 6 LowStress
16 4 LowStress
17 2 LowStress
18 2 LowStress
> AnovaResults <- aov(values ~ ind, data= Stacked_Groups)
> AnovaResults
Call:
aov(formula = values ~ ind, data = Stacked_Groups)

Terms:
ind Residuals
Sum of Squares 82.11111 28.83333
Deg. of Freedom 2 15

Residual standard error: 1.386442
Estimated effects may be unbalanced
> summary(AnovaResults)
Df Sum Sq Mean Sq F value Pr(>F)
ind 2 82.11 41.06 21.36 4.08e-05 ***
Residuals 15 28.83 1.92
—
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1