R-Studio Midterm 2

Question 1

regression

Answer 1

lm(dv ~ iv, data = dataset)

Question 2

adding categorical variable to regression

Answer 2

lm(dv ~ iv, as.factor(variable), data = dataset)

Question 3

adding binary variable to regression

Answer 3

lm(dv ~ iv + variable 1 + variable 2, data = dataset)

Question 4

adding interaction to regression

Answer 4

lm(dv ~ iv, as.factor(variable), dv:as.factor(variable), data = dataset)

Question 5

quadratic lm model

Answer 5

lm(dv ~ iv + I(iv^2), data = dataset)

Question 6

generalized linear model

Answer 6

glm(dv ~ iv, data = dataset, family = binominal (link = “logit”))

Question 7

adding a covariate to generalized linear model

Answer 7

glm(dv ~ iv + as.factor(variable), data - dataset, family = binominal (link = “logit”))

Question 8

adding an interaction to generalized linear model

Answer 8

glm(dv ~ iv + as.factor(variable) + iv:as.factor(variable), data - dataset, family = binominal (link = “logit”))

Question 9

MANOVA

Answer 9

MANOVA(cbind(dv1, dv2, data= dataset)

Question 10

Linear Discriminant Analysis

Answer 10

lda(iv ~ dv1 + dv2 + dv3, data = dataset)

Question 11

predicting for LDA

Answer 11

head(predict(lda)$posterior)

Question 12

confusion matrix

Answer 12

table(predict(lda)$class, dataset$iv)