This question is about working with temporal data. The example data is on pedestrian counts in the city of Melbourne. What time periods of Melbourne pedestrian traffic are extracted by the code below?

Select all answers that you think are correct. Incorrect answers are penalised.

library(lubridate)
library(rwalkr)
ped_2020 <- melb_walk(from=Sys.Date() - 7L)
ped_2019 <- melb_walk(from=Sys.Date() - 30L - years(1), to=Sys.Date() - years(1))

The following question is about visualisation.

The data shows calories of a selection of chocolate bars, 100g equivalents. Which of the following statements are true?

The following question is about visualisation.

The data shows calories of a selection of chocolate bars, 100g equivalents. Calories mapped to the vertical axis. If you are wanting the reader to compare the inter quantile range of calories of milk and dark chocolates, which part of the plot do you need to observe?

The following question is about tidy data. The table below contains looks at crime occurrence in different locations across Victoria:

What proportion of the crimes were recorded in the Monash LGA?

Incorrect answers are penalised.

The following question is about tidy data. The table below contains looks at crime occurrence in different locations across Victoria:

What is the proportion of crimes that entered through the front door?

Hint: If a data set contains "NA" values, it means the entries are missing. You can ignore these missing values here.

The following question is about tidy data. The table below contains looks at crime data in different locations across Victoria:

As usually we need to first inspect the variables and observations in this data set. What is the dimension of the data set?