Introduction to Data Science Questions (Data Fundamentals)
1. Data Science is primarily concerned with:
a) Software development
b) Extracting knowledge and insights from data
c) Computer hardware maintenance
d) Network configuration
2. Which of the following is NOT a stage in the Data Science process?
a) Data collection
b) Data visualization
c) Data destruction
d) Model evaluation
3. The term “Big Data” refers to:
a) Data that is stored in large servers
b) Data too large or complex for traditional processing methods
c) Data generated by small companies only
d) Data stored on personal computers
4. Which of the following languages is most commonly used in Data Science?
a) C
b) Python
c) PHP
d) Swift
5. Structured data is typically stored in:
a) Text documents
b) Databases and spreadsheets
c) Images and videos
d) Audio files
6. Which type of data includes social media posts and videos?
a) Structured
b) Semi-structured
c) Unstructured
d) Numeric
7. Data cleaning involves:
a) Making data more complex
b) Removing or correcting inaccurate records
c) Increasing the data size
d) Encrypting data
8. A missing value in a dataset is represented by:
a) Zero
b) NULL or NaN
c) Infinity
d) A negative number
9. Outliers in data are:
a) The most frequent values
b) Values that deviate significantly from other observations
c) Normal data points
d) Missing data
10. Data visualization helps in:
a) Hiding data errors
b) Communicating data insights effectively
c) Slowing down computation
d) Generating random data
11. A histogram is used to represent:
a) Relationships between two variables
b) Distribution of a single variable
c) Time-series data
d) Text data
12. A correlation coefficient close to 1 indicates:
a) A weak positive relationship
b) A strong positive relationship
c) No relationship
d) A strong negative relationship
13. Machine Learning is a subset of:
a) Artificial Intelligence
b) Web Development
c) Data Mining only
d) Database Management
14. Supervised learning uses:
a) Unlabeled data
b) Labeled data
c) Text data only
d) Random data
15. Which of the following is an example of supervised learning?
a) K-means clustering
b) Linear regression
c) Association rule mining
d) Principal component analysis
16. Unsupervised learning is used when:
a) The data labels are known
b) The data labels are unknown
c) The dataset is too small
d) There is no data cleaning
17. SQL is primarily used for:
a) Web design
b) Data querying and management
c) Image recognition
d) Statistical plotting
18. Which of these is a cloud-based platform for data storage and analysis?
a) Google Drive
b) Amazon Web Services (AWS)
c) Photoshop
d) CorelDraw
19. Data privacy refers to:
a) Hiding all data from the public
b) Protecting sensitive information from misuse
c) Collecting as much data as possible
d) Selling user data for profit
20. Bias in machine learning models occurs when:
a) The dataset is very large
b) The model performs equally for all groups
c) Certain groups or outcomes are unfairly favored
d) The model is unsupervised
21. Which of the following is a real-world application of Data Science?
a) Movie recommendation systems
b) Manual bookkeeping
c) Typewriters
d) Handwritten letters
22. Ethics in data science ensures:
a) Manipulation of data for desired results
b) Responsible use and interpretation of data
c) Restriction of data to scientists only
d) Avoiding automation
23. The main difference between Data Science and Statistics is that Data Science:
a) Focuses only on mathematical theory
b) Integrates computing, automation, and real-world data handling
c) Is unrelated to statistics
d) Ignores data interpretation