FIT1043 Introduction to data science 125 ACTUAL EXAM POSSIBLE
QUESTIONS AND ANSWERS 2025 Monash University
Correct 125
Incorrect
Your answers
Term
, For simple models with large bias, the variance is small. For complex
models with small bias, the variance would be small except for the
occasion when it goes wild, leading to a large variance overall.
It is a continual process that uses data policies and procedures to ensure that
data is properly managed. Furthermore, it is used to ensure that the data is
formatted correctly so it can extract knowledge/value.
Don't know?
2 of 125
Term
What is the difference between a data scientist and a chief data
scientist?
Give this one a try later!
Integrity Constraint Violation normally checks whether data logically makes
sense or not, depending on context and are logical faults between columns,
while irregularity checks whether data is valid or not according to the logical
faults within the data.
Data science is the extraction of knowledge/value from data and is the
continuation of the field of data mining and predictive analysis through a data
lifecycle.
The standard value chain is the process of a data science project. The steps
collection, wrangle, analyse and present happen respectively with engineering,
governance and operationalisation happening throughout the process.
, A data scientist is involved in the direct processes of extracting
knowledge/value from the data. A chief data scientist however involves
themselves in data management, engineering and data science goals.
Don't know?
3 of 125
Definition
Metadata is structured information that describes, explains, locates
or makes it easier to retrieve use or manage an information resource,
essentially data for data. Eg. EXIF Images. There are three types of
metadata, descriptive (content for identification and retrieval),
structural (documents relationships and links), administrative (to
manage information).
Give this one a try later!
What is feature scaling? What is metadata?
What is the learning theory? What is deep learning?
Don't know?
4 of 125
Term
, Referring to the two slides about the car industry: First, they
underwent a digitization process, followed by a datafication process.
Using a word or short phrase, name a non-automotive industry that
have had similar developments in recent decades. How do you
expect the datafication process to change retail industry?
Give this one a try later!
This code merges two dataframes More effective in providing
by a common key variable/s customised products
It permanently changes the dataset
Fitting a linear regression in R.
if this piece of code is included.
Don't know?
5 of 125
Term
> myTable[1,]
What does this code do?
Give this one a try later!
Accessing all rows and columns by
Fitting a linear regression in R.
omitting comma.
Accessing first row and all the
Accessing a specific cell in the first
columns by appending
row.
comma.
QUESTIONS AND ANSWERS 2025 Monash University
Correct 125
Incorrect
Your answers
Term
, For simple models with large bias, the variance is small. For complex
models with small bias, the variance would be small except for the
occasion when it goes wild, leading to a large variance overall.
It is a continual process that uses data policies and procedures to ensure that
data is properly managed. Furthermore, it is used to ensure that the data is
formatted correctly so it can extract knowledge/value.
Don't know?
2 of 125
Term
What is the difference between a data scientist and a chief data
scientist?
Give this one a try later!
Integrity Constraint Violation normally checks whether data logically makes
sense or not, depending on context and are logical faults between columns,
while irregularity checks whether data is valid or not according to the logical
faults within the data.
Data science is the extraction of knowledge/value from data and is the
continuation of the field of data mining and predictive analysis through a data
lifecycle.
The standard value chain is the process of a data science project. The steps
collection, wrangle, analyse and present happen respectively with engineering,
governance and operationalisation happening throughout the process.
, A data scientist is involved in the direct processes of extracting
knowledge/value from the data. A chief data scientist however involves
themselves in data management, engineering and data science goals.
Don't know?
3 of 125
Definition
Metadata is structured information that describes, explains, locates
or makes it easier to retrieve use or manage an information resource,
essentially data for data. Eg. EXIF Images. There are three types of
metadata, descriptive (content for identification and retrieval),
structural (documents relationships and links), administrative (to
manage information).
Give this one a try later!
What is feature scaling? What is metadata?
What is the learning theory? What is deep learning?
Don't know?
4 of 125
Term
, Referring to the two slides about the car industry: First, they
underwent a digitization process, followed by a datafication process.
Using a word or short phrase, name a non-automotive industry that
have had similar developments in recent decades. How do you
expect the datafication process to change retail industry?
Give this one a try later!
This code merges two dataframes More effective in providing
by a common key variable/s customised products
It permanently changes the dataset
Fitting a linear regression in R.
if this piece of code is included.
Don't know?
5 of 125
Term
> myTable[1,]
What does this code do?
Give this one a try later!
Accessing all rows and columns by
Fitting a linear regression in R.
omitting comma.
Accessing first row and all the
Accessing a specific cell in the first
columns by appending
row.
comma.
