R Year 2

Question 1

t test

Answer 1

t.test(vector, mu = no, alternative = “g”)

Question 2

mu

Answer 2

Average

Question 3

Alternative =

Answer 3

l for lower
g for greater

Question 4

Can a t-test be used?

Answer 4

Do a variance test

Question 5

Variance test

Answer 5

var.test(height$female, height$male) compares the variances of two groups of data to see if a t test can be used

Question 6

Is it normal

Answer 6

shapiro test

Question 7

Shapiro test

Answer 7

Shapiro.test() compares data to a normal distribution

Question 8

equation for chi squared

Answer 8

sum(((chi$observed-chi$expected)^2)/chi$expected)

Question 9

multiple linear regression

Answer 9

model1 = lm(dv ~ iv1+iv2+iv3….etc, dataset)
Compares dv to each iv within the dataset.

Question 10

Remove rows containing 0 values

Answer 10

na.omit(data)

Question 11

Anova

Answer 11

anova(data)
Number within the range is not significant difference

Question 12

AIC

Answer 12

AIC = step(model1, direction = “backward”)

Question 13

checking by going forward

Answer 13

forward = step(naive, scope = dv ~ iv1+iv2+iv3…, direction = “forward”)

where naive is the simplest model = lm(iv~1, data)

Question 14

Give all the data the same scale

Answer 14

scale(data)

Question 15

Correlation PCA

Answer 15

PCA = princomp(data, cor=TRUE)

Question 16

Covariance PCA

Answer 16

PCA = princomp(data)

Question 17

Visualising PCA

Answer 17

screeplot(PCA)
Has elbow

Question 18

Way to see first two PCs

Answer 18

biplot(PCA)

Question 19

Influence of each component on original variables

Answer 19

loadings(PCA)

Question 20

Triangular matrix of differences

Answer 20

matrix1 = dist(data)

Question 21

Make clusters using matrix

Answer 21

clusters = hclust(matrix1)
can add in method = “single”, “complete”, etc default is euclidean

Question 22

Create dendrogram

Answer 22

plot(clusters)

Question 23

divide dendrogram into 4 clusters

Answer 23

rect.hclust(clusters, k=4, border=”red”)

Question 24

Make triangular distance matrix of dendrogram

Answer 24

cophenetic = cophenetic(clusters)

Question 25

Find cophenetic correlation

Answer 25

cor(matrix1, cophenetic)
Higher value given is better