The dataframe students contains information on 1000 students, with the columns marks, age, country of origin, study style, ATAR and gender.

Assuming tidyverse has been loaded, what ggplot would NOT generate an error message?

Note:

Marks are measured 0-100 (from mid semester exam)
Age is number of days from birth
Country of Origin is Australia, China etc
Study Style is: independent or dependent
ATAR is Australia Tertiary Admission Rank ( a number between 0 and 99.95)
Gender is Male, Female, NotSpecified etc

Question

The dataframe students contains information on 1000 students, with the columns marks, age, country of origin, study style, ATAR and gender.

Assuming tidyverse has been loaded, what ggplot would NOT generate an error message?

Note:

Marks are measured 0-100 (from mid semester exam)
Age is number of days from birth
Country of Origin is Australia, China etc
Study Style is: independent or dependent
ATAR is Australia Tertiary Admission Rank ( a number between 0 and 99.95)
Gender is Male, Female, NotSpecified etc

BlackTom AI · Accepted Answer

The question asks which ggplot call would NOT generate an error when using the dataframe named 'students' with several columns. 
Option 1: ggplot(aes(students$age))
- This is not valid because ggplot typically requires a data argument (the dataset) and an aesthetic mapping supplied via aes(), usually in the form ggplot(data, aes(...)). Here, there is no data argument provided, and the aes() call is not attached to a ggplot object with a data source, so this will produce an error about a missing data frame or improper usage. 
Option 2: ggplot(aes(students$age))+geom_hist()
- This has two issues. First, there is no explicit data= argument or base ggplot object to attach the aesthetics to, similar to option 1. Second, the function name for a histogram is geom_histogram(), not geom_hist(), so even with a data source this would fail due to the incorrect geom function name. Overall, this would error out both on syntax and on function naming. 
Option 3: ggplot(students)
- This is valid. It creates a ggplot object with the data source set to the students data frame. Although it has no aesthetic mappings yet, it is a properly formed call and will not produce an error by itself. Users can then add layers and mappings (e.g., + aes(x=age) + geom_histogram()) without immediate error. 
Option 4: ggplot(students$marks)
- This is invalid because the first argument to ggplot should be a data frame (or data-like object) containing the variables, not a vector extracted from the data frame. Supplying a vector as the data argument does not satisfy ggplot's expectations and will trigger an error. 
In summary, Option 3 is the only call that integrates cleanly with ggplot’s expected usage pattern by providing the data frame as the data source, while the other options misuse the function signature or names and would result in errors.

DATA1001/1901 (ND) Revision Quiz 2

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