Data Science Fundamentals

Test your knowledge on key concepts and techniques in the field of data science, from data lifecycle to machine learning algorithms.

Flashcards36 cardsFPractice quizPHost liveL

Questions 36

Answers

1
What is sentiment analysis?
Numerical analysis
Data storage
Data cleaning
Text processing
2
Which is a common data source?
Movies
Databases
Books
Paintings
3
What does data privacy protect?
Personal information
Public information
Weather data
Company secrets
4
What is variance in statistics?
Middle value
Spread of data points
Most frequent value
Average of values
5
What is the mean in statistics?
Average of values
Middle value
Most frequent value
Spread of data
6
What is a Python variable?
Comment
Output
Storage location
Data type
7
What does a histogram display?
Distribution of a variable
Trends over time
Relationships between variables
Categorical data
8
What is probability?
Certainty
Randomness
Likelihood of event
Impossibility
9
What is the primary goal of data science?
To extract knowledge
To collect data
To clean data
To visualize data
10
What is a neural network inspired by?
Computer algorithms
Human brain structure
Statistical models
Data visualization
11
What does a line graph show?
Categorical comparisons
Trends over time
Single variable analysis
Distribution of data
12
Which technique helps mitigate bias?
Diverse data collection
Random sampling
Ignoring data
Using only one source
13
True or false: Data cleaning is optional.
False
True
14
What is the role of fairness metrics?
To enhance privacy
To ignore bias
To complicate models
To ensure equal performance
15
What is a neural network inspired by?
Weather patterns
Human brain
Computer
Animal instincts
16
What does NumPy specialize in?
Data visualization
Web development
Numerical operations
Text processing
17
What does mean measure?
Middle value
Average value
Most frequent value
Spread of values
18
Which is a common source of data?
Surveys
Only APIs
Only sensors
Only databases
19
Why is data cleaning essential?
To delete data
To ensure accuracy
To add errors
To confuse analysts
20
True or false: Data cleaning is optional for reputable data.
False
True
21
Why is data visualization crucial?
To delete data
To communicate findings
To confuse viewers
To hide data
22
What is the first step in the data science lifecycle?
Data Presentation
Data Analysis
Data Collection
Data Cleaning
23
What does a decision tree represent?
A flowchart-like structure
A data collection method
A linear equation
A type of visualization
24
What is a decision tree?
Data cleaning
Data storage
Flowchart structure
Random process
25
What can cause bias in data?
Random errors
Complete data
Systematic errors
Perfect data
26
What graph shows temperature trends?
Bar chart
Line graph
Scatterplot
Histogram
27
What is a histogram used for?
Trends over time
Relationship between variables
Single variable distribution
Category comparison
28
Which library is used for data manipulation?
NumPy
Pandas
Scikit-learn
Matplotlib
29
What does regression predict?
Continuous output
Binary outcome
Random value
Categorical label
30
Which method helps in understanding complex data?
Data Collection
Data Cleaning
Data Analysis
Data Visualization
31
What is the purpose of data cleaning?
To ensure data quality
To ignore errors
To make data messy
To complicate analysis
32
What does bias in data lead to?
Unfair outcomes
Accurate results
Better insights
Fair outcomes
33
True or false: A scatterplot shows single variable distribution.
True
False
34
What is a fairness metric?
Storage solution
Visualization method
Bias detection
Data cleaning tool
35
What is a real-world application of data science?
Healthcare
Painting
Cooking
Gardening
36
What is the first step in the data lifecycle?
Data Analysis
Data Cleaning
Data Collection
Data Presentation

Data Science Fundamentals Flashcards | StudBud

Data Science Fundamentals

36 termsStudBud Administration

Test your knowledge on key concepts and techniques in the field of data science, from data lifecycle to machine learning algorithms.

Flashcards36 cardsFPractice quizPHost liveL

Questions 36

Answers

1
What is sentiment analysis?
Numerical analysis
Data storage
Data cleaning
Text processing
2
Which is a common data source?
Movies
Databases
Books
Paintings
3
What does data privacy protect?
Personal information
Public information
Weather data
Company secrets
4
What is variance in statistics?
Middle value
Spread of data points
Most frequent value
Average of values
5
What is the mean in statistics?
Average of values
Middle value
Most frequent value
Spread of data
6
What is a Python variable?
Comment
Output
Storage location
Data type
7
What does a histogram display?
Distribution of a variable
Trends over time
Relationships between variables
Categorical data
8
What is probability?
Certainty
Randomness
Likelihood of event
Impossibility
9
What is the primary goal of data science?
To extract knowledge
To collect data
To clean data
To visualize data
10
What is a neural network inspired by?
Computer algorithms
Human brain structure
Statistical models
Data visualization
11
What does a line graph show?
Categorical comparisons
Trends over time
Single variable analysis
Distribution of data
12
Which technique helps mitigate bias?
Diverse data collection
Random sampling
Ignoring data
Using only one source
13
True or false: Data cleaning is optional.
False
True
14
What is the role of fairness metrics?
To enhance privacy
To ignore bias
To complicate models
To ensure equal performance
15
What is a neural network inspired by?
Weather patterns
Human brain
Computer
Animal instincts
16
What does NumPy specialize in?
Data visualization
Web development
Numerical operations
Text processing
17
What does mean measure?
Middle value
Average value
Most frequent value
Spread of values
18
Which is a common source of data?
Surveys
Only APIs
Only sensors
Only databases
19
Why is data cleaning essential?
To delete data
To ensure accuracy
To add errors
To confuse analysts
20
True or false: Data cleaning is optional for reputable data.
False
True
21
Why is data visualization crucial?
To delete data
To communicate findings
To confuse viewers
To hide data
22
What is the first step in the data science lifecycle?
Data Presentation
Data Analysis
Data Collection
Data Cleaning
23
What does a decision tree represent?
A flowchart-like structure
A data collection method
A linear equation
A type of visualization
24
What is a decision tree?
Data cleaning
Data storage
Flowchart structure
Random process
25
What can cause bias in data?
Random errors
Complete data
Systematic errors
Perfect data
26
What graph shows temperature trends?
Bar chart
Line graph
Scatterplot
Histogram
27
What is a histogram used for?
Trends over time
Relationship between variables
Single variable distribution
Category comparison
28
Which library is used for data manipulation?
NumPy
Pandas
Scikit-learn
Matplotlib
29
What does regression predict?
Continuous output
Binary outcome
Random value
Categorical label
30
Which method helps in understanding complex data?
Data Collection
Data Cleaning
Data Analysis
Data Visualization
31
What is the purpose of data cleaning?
To ensure data quality
To ignore errors
To make data messy
To complicate analysis
32
What does bias in data lead to?
Unfair outcomes
Accurate results
Better insights
Fair outcomes
33
True or false: A scatterplot shows single variable distribution.
True
False
34
What is a fairness metric?
Storage solution
Visualization method
Bias detection
Data cleaning tool
35
What is a real-world application of data science?
Healthcare
Painting
Cooking
Gardening
36
What is the first step in the data lifecycle?
Data Analysis
Data Cleaning
Data Collection
Data Presentation