R studio

Question 1

str()

Answer 1

way of summarizing the data

Question 2

count()

Answer 2

counts variables

Question 3

group_by()

Answer 3

• groups a dataset
• whatever you do next to the dataset will be done separately for each group
• e.g. each gender

Question 4

summarise ()

Answer 4

will create a table with summary stats you have requested

Question 5

inner_join()

Answer 5

Uses matching rows from each data set to join them
e.g.
full_dat <- inner_join(x = demographic_data,
y = score_data,
by = “Participant”)

Question 6

select ()

Answer 6

Creates a new dataset with just the columns you want
If you want to say which ones you don’t want use -variable.

Question 7

filter ()

Answer 7

Used to pick which rows of data you want to keep based on one or more criteria

Question 8

mutate()

Answer 8

Changing the data set
For example adding a new variable:
full_data <- full_data %>%
mutate(gender_coded = factor(gender,
levels = c(2,1, 3),
labels = c(“Man”, “Woman”, “Nonbinary”)))

Question 9

How do you create a scatter plot

Answer 9

ggplot( data set, aes(x = variable, y = variable)) + geom_point()

Question 10

How do you add a line of best fit to a scatter graph?

Answer 10

geom_(smooth)

Question 11

pivot_longer()

Answer 11

transforms data from wide-form to long-form

Question 12

How do you use pivot_longer?

Answer 12

pivot_longer (cols = first column : last column,
names to = “coloumn name”,
values to = “column name”

Question 13

as.factor()

Answer 13

Overwrites whatever is in that column as a factor

Question 14

as.character()

Answer 14

overwrites whatever is in that column as a character

Question 15

dbinom()

Answer 15

density function; gives you the probability of x successes given the number of trails and the probability of success on a single trial

Question 16

pbinom()

Answer 16

Probability distribution fucntion: gives you the cumulative probability of getting a number of successes below a certain cut-off point, given the size and the probability

Question 17

qbinom ()

Answer 17

the quantile function: is the opposite of pbinom(), in that gives you the x axis value for a given probability p, plus given the size and prob, that is if the probability of flipping a head is .5, how many heads would you expect to get with 10 flips

Question 18

dnorm()

Answer 18

used for calculating the probability of a specific value

Question 19

pnorm()

Answer 19

for calculating the probability of getting at least or at most a specific value

Question 20

qnorm()

Answer 20

the quantile function, for calculating specific values associated with a given probability