Here is the data needed for this question:

Herbivore total_cover

Full 52.5

Full 51.25

Full 36.25

Full 23.75

Full 7.5

Full 38

Full 33.75

Open Access 56.25

Open Access 70

Open Access 61.25

Open Access 63.25

Open Access 68.75

Open Access 86

Open Access 100

Partial 33.75

Partial 18.75

Partial 16.25

Partial 5

Partial 1.25

Partial 29

Partial 36.25

Full 91.5

Full 97.75

Full 96.75

Full 100

Full 100

Full 99.25

Full 97.5

Open Access 85.5

Open Access 76.25

Open Access 50

Open Access 60

Open Access 28.75

Open Access 58

Open Access 58.75

Partial 88.5

Partial 91.25

Partial 72.5

Partial 88.75

Partial 72.5

Partial 92.75

Partial 88.75

Full 56.25

Full 61.25

Full 10

Full 6.25

Full 8.75

Full 57.75

Full 69.25

Open Access 68.75

Open Access 68.75

Open Access 46.25

Open Access 57

Open Access 23.25

Open Access 50

Open Access 43.75

Partial 60

Partial 63

Partial 59.5

Partial 56.25

Partial 24.5

Partial 53

Partial 66.25

Full 73.25

Full 90.75

Full 100

Full 100

Full 99.75

Full 100

Full 100

Open Access 56.25

Open Access 58.75

Open Access 37.5

Open Access 40

Open Access 7.5

Open Access 49

Open Access 49.5

Partial 77.25

Partial 76.25

Partial 60.75

Partial 45

Partial 18.75

Partial 56.5

Partial 50.5

Full 18.75

Full 71.25

Full 89.5

Full 91.25

Full 47.5

Full 68

Full 72.5

Open Access 17.5

Open Access 43.75

Open Access 41.25

Open Access 38.75

Open Access 4.5

Open Access 22

Open Access 15

Partial 7.5

Partial 42.5

Partial 37.5

Partial 23.75

Partial 21.75

Partial 43

Partial 41.25

*this data should be copied into an excel document and then put into r*

When you look at the boxplot you created in Q1.c, you notice that, while the sample means are different, there is also a big spread of total vegetation covers within each treatment. What would happen to your conclusions if you for instance decrease the sample size from 105 to only 30 samples? Explore this by running your code to obtain the ANOVA table using the original data several times with a data set that randomly selects 30 rows from the original data set:

herb_subset1 = herbivore_exclosure[sample(nrow(herbivore_exclosure), size = 30), ]

herb_subset2 = herbivore_exclosure[sample(nrow(herbivore_exclosure), size = 30), ]

herb_subset3 = herbivore_exclosure[sample(nrow(herbivore_exclosure), size = 30), ]

Explain your answer by referring to your 3 random subsamples and associated analyses (include the 3 R ANOVA outputs in your answer).

Thank you in advance