About this Study Set
This study set covers Data Science through
20 practice questions.
Essential knowledge covering the fundamental concepts, tools, and methodologies of data science. Every question includes the correct answer so you can learn as you go — pick any format above to get started.
Questions & Answers
Browse all 20 questions from the
Data Science Foundations study set below.
Each question shows the correct answer — select a study format above to practice interactively.
1
Which programming language is most commonly cited as the primary language for data science and machine learning tasks?
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A
Java
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B
Python
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C
HTML
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D
Assembly
2
What is the primary purpose of a 'train-test split' in machine learning?
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A
To format the data for Excel
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B
To evaluate model performance on unseen data
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C
To increase the size of the dataset
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D
To delete outliers from the database
3
In a confusion matrix, what does a 'False Positive' represent?
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A
Correctly identifying a positive case
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B
Failing to identify a positive case
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C
Predicting a positive result when the actual result is negative
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D
Predicting a negative result when the actual result is positive
4
Which library is widely used in Python for data manipulation and analysis, providing structures like DataFrames?
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A
Pandas
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B
PyQt
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C
Tkinter
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D
Requests
5
What is the term for a subset of artificial intelligence that involves training algorithms to learn patterns from data?
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A
Cloud Computing
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B
Machine Learning
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C
Quantum Physics
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D
Blockchain
6
What is the main goal of 'Data Cleaning' in the data science pipeline?
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A
To encrypt the data for security
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B
To visualize the data in charts
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C
To fix or remove incorrect, corrupted, or duplicate data
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D
To compress the data for faster storage
7
Which statistical measure represents the most frequently occurring value in a dataset?
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A
Mean
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B
Median
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C
Mode
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D
Range
8
What does SQL stand for in the context of database management?
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A
Standard Query Language
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B
Structured Query Language
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C
Simple Quality Language
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D
System Query Logic
9
In supervised learning, what kind of data is required to train a model?
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A
Unlabeled data
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B
Labeled data
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C
Random noise
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D
Deleted files
10
Which visualization tool is best suited for showing the distribution of a single continuous variable?
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A
Histogram
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B
Pie chart
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C
Line chart
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D
Network graph
11
What is the 'Overfitting' phenomenon in machine learning?
-
A
When a model performs poorly on training data
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B
When a model learns the noise in training data too well, failing to generalize
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C
When a model is too simple to capture the pattern
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D
When a model uses too much RAM
12
Which of the following is considered a 'categorical' variable?
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A
Height in centimeters
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B
Blood type (A, B, AB, O)
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C
Time taken to run a race
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D
Annual income
13
What is 'Data Mining'?
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A
Manually typing data into a spreadsheet
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B
The process of discovering patterns in large data sets
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C
The physical extraction of minerals
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D
Hardware installation for servers
14
Which Python library is the standard for creating static, animated, and interactive visualizations?
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A
Matplotlib
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B
TensorFlow
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C
PyTorch
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D
Flask
15
What is the 'null hypothesis' in statistical testing?
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A
The assumption that there is no effect or no difference
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B
The assumption that the data is corrupted
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C
The initial guess of the researcher
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D
The final conclusion of an experiment
16
What type of chart is best for showing the relationship between two continuous variables?
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A
Bar chart
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B
Scatter plot
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C
Histogram
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D
Area chart
17
In data science, what is a 'Feature'?
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A
The final output of a model
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B
An input variable used in making predictions
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C
The name of the data scientist
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D
The computer hardware used
18
What is 'Big Data' typically characterized by?
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A
Volume, Velocity, and Variety
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B
Speed, Memory, and Pixels
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C
Color, Weight, and Sound
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D
Price, Size, and Name
19
Which algorithm is a popular choice for classification tasks and is based on the idea of drawing a boundary between classes?
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A
Logistic Regression
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B
Linear Regression
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C
K-Means Clustering
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D
Principal Component Analysis
20
What is the purpose of 'Normalization' in data preprocessing?
-
A
To scale numerical values to a common range
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B
To translate text into another language
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C
To convert all data to binary
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D
To increase the data file size
