CBSE Class 9 AI Chapter 2 MCQs with Answers (2026-27) | Data Literacy | 50 Important Questions
Class 9 · Artificial Intelligence
Q1. What is the definition of Data Literacy?
A. The ability to write computer code.
B. The ability to understand, interpret, and communicate with data.
C. The ability to build hardware components.
D. The ability to memorize large datasets.
Show Answer
Answer: B. The ability to understand, interpret, and communicate with data.
Explanation: Data Literacy is the ability to read, understand, analyze, interpret, and communicate information from data. It enables people to make informed decisions based on evidence rather than assumptions.
Q2. In the Data Pyramid, which level represents data in its raw, unprocessed form?
A. Information
B. Knowledge
C. Wisdom
D. Data
Show Answer
Answer: D. Data
Explanation: Data is the lowest level of the Data Pyramid. It consists of raw facts and figures that have little meaning until they are processed.
Q3. Which stage of the Data Pyramid answers the questions "Who, What, When, and Where"?
A. Wisdom
B. Knowledge
C. Information
D. Raw Facts
Show Answer
Answer: C. Information
Explanation: Information is processed data that provides meaning by answering questions such as Who, What, When, and Where.
Q4. Which level of the Data Pyramid helps us understand "how" things are happening?
A. Data
B. Wisdom
C. Knowledge
D. Information
Show Answer
Answer: C. Knowledge
Explanation: Knowledge is obtained by analyzing information and identifying relationships or patterns. It explains how events occur.
Q5. Wisdom is the highest level of the Data Pyramid because it helps us understand:
A. How much data we have.
B. Where the data came from.
C. Why things happen in a particular way.
D. When the data was collected.
Show Answer
Answer: C. Why things happen in a particular way.
Explanation: Wisdom is the ability to make sound decisions by understanding the reasons behind events and applying knowledge effectively.
Q6. "Cultivating Data Literacy" refers to:
A. Developing only mathematical skills.
B. Continuously improving the ability to understand and use data.
C. Learning only statistical formulas.
D. Memorizing datasets.
Show Answer
Answer: B. Continuously improving the ability to understand and use data.
Explanation: Cultivating Data Literacy means developing and strengthening the skills required to collect, interpret, analyze, and communicate data effectively.
Q7. In the traffic light example, seeing the traffic signal turn red represents:
A. Wisdom
B. Knowledge
C. Information
D. Data
Show Answer
Answer: C. Information
Explanation: The observation that the traffic light has turned red is processed information that helps us understand the current situation.
Q8. In the same traffic light example, deciding to stop the vehicle represents:
A. Data
B. Information
C. Knowledge
D. Wisdom
Show Answer
Answer: D. Wisdom
Explanation: Wisdom is the ability to apply knowledge and information to make the correct decision—in this case, stopping the vehicle safely.
Q9. A decision is only as good as the ________ it is based on.
A. Spreadsheet
B. Knowledge
C. Computer
D. Price
Show Answer
Answer: B. Knowledge
Explanation: Good decisions depend on accurate knowledge, which is developed from meaningful information and reliable data.
Q10. Data Literacy enables informed ________ and critical thinking.
A. Programming
B. Web Scraping
C. Decision-making
D. Data Augmentation
Show Answer
Answer: C. Decision-making
Explanation: Data Literacy helps individuals analyze evidence, think critically, and make well-informed decisions in everyday life and professional situations.
Q11. What is the practice of protecting digital information from unauthorized access throughout its lifecycle?
A. Data Literacy
B. Data Security
C. Data Acquisition
D. Data Interpretation
Show Answer
Answer: B. Data Security
Explanation: Data Security involves protecting digital information from unauthorized access, theft, corruption, or misuse by using appropriate security measures.
Q12. Data Privacy and Data Security are the same thing.
A. True
B. False
Show Answer
Answer: B. False
Explanation: Data Privacy deals with how personal information is collected and used, whereas Data Security focuses on protecting data from unauthorized access and cyber threats.
Q13. Which of the following is a good cyber security practice?
A. Sharing your phone number on social media.
B. Ignoring software updates.
C. Keeping passwords and security questions private.
D. Clicking every unknown link received by email.
Show Answer
Answer: C. Keeping passwords and security questions private.
Explanation: Strong passwords and keeping login credentials confidential are essential practices for protecting online accounts and personal data.
Q14. Why is Data Privacy important in Artificial Intelligence?
A. AI does not use any data.
B. AI systems often use personal data that must be handled responsibly.
C. AI only works with public data.
D. AI automatically deletes all collected data.
Show Answer
Answer: B. AI systems often use personal data that must be handled responsibly.
Explanation: AI applications frequently process personal information. Protecting users' privacy is an important ethical responsibility while developing AI systems.
Q15. Which ethical principle means taking responsibility for the proper use of collected data?
A. Bias
B. Consent
C. Accountability
D. Transparency
Show Answer
Answer: C. Accountability
Explanation: Accountability means individuals and organizations are responsible for the way they collect, store, process, and use data.
Q16. Protecting the identity of the person whose data is collected is known as:
A. Transparency
B. Anonymity
C. Bias
D. Accuracy
Show Answer
Answer: B. Anonymity
Explanation: Anonymity ensures that personal information cannot be linked back to an individual, thereby protecting their identity.
Q17. Which ethical principle requires informing users about how their data will be collected and used?
A. Consent
B. Transparency
C. Accountability
D. Privacy
Show Answer
Answer: B. Transparency
Explanation: Transparency means openly explaining how data is collected, stored, processed, and used so that users clearly understand its purpose.
Q18. Taking permission before collecting an individual's personal data is called:
A. Consent
B. Bias
C. Security
D. Literacy
Show Answer
Answer: A. Consent
Explanation: Consent is the voluntary permission given by an individual before their personal information is collected or used.
Q19. What should you do if you receive a suspicious message asking for your bank account details?
A. Share the details immediately.
B. Forward it to friends.
C. Ignore the request and report it if necessary.
D. Post it on social media.
Show Answer
Answer: C. Ignore the request and report it if necessary.
Explanation: Never share banking or personal information through suspicious messages. Such requests are often attempts at fraud or phishing.
Q20. Avoiding cyberbullying and using respectful language online is an example of:
A. Data Acquisition
B. Data Security
C. Good Cyber Security Practices
D. Data Interpretation
Show Answer
Answer: C. Good Cyber Security Practices
Explanation: Responsible online behavior, including avoiding cyberbullying and respecting others, contributes to a safer and more secure digital environment.
Q21. The process of searching for and downloading relevant data from the internet is called:
A. Data Generation
B. Data Discovery
C. Data Augmentation
D. Data Preprocessing
Show Answer
Answer: B. Data Discovery
Explanation: Data Discovery is the process of searching, identifying, and obtaining useful datasets from online sources for analysis or AI projects.
Q22. What does Data Augmentation mean?
A. Deleting existing data
B. Increasing the amount of data by creating modified versions of existing data
C. Recording data using sensors
D. Collecting data through interviews
Show Answer
Answer: B. Increasing the amount of data by creating modified versions of existing data
Explanation: Data Augmentation creates additional training data by making slight changes, such as rotating or flipping images, which improves the performance of AI models.
Q23. Recording temperature readings using sensors is an example of:
A. Data Discovery
B. Data Augmentation
C. Data Generation
D. Data Visualization
Show Answer
Answer: C. Data Generation
Explanation: Data Generation involves collecting new data directly through sensors, experiments, observations, or other measuring devices.
Q24. Surveys, interviews, and experiments are examples of:
A. Primary Data Sources
B. Secondary Data Sources
C. Data Cleaning
D. Data Visualization
Show Answer
Answer: A. Primary Data Sources
Explanation: Primary Data is collected directly by the researcher for a specific purpose through surveys, interviews, observations, or experiments.
Q25. Which of the following is a Secondary Data Source?
A. A survey conducted by you
B. An interview taken by you
C. Kaggle datasets
D. Your classroom observations
Show Answer
Answer: C. Kaggle datasets
Explanation: Secondary Data refers to information that has already been collected by someone else. Kaggle provides thousands of publicly available datasets.
Q26. What is Web Scraping?
A. Designing websites
B. Collecting data automatically from websites using software
C. Creating web pages
D. Searching the internet manually
Show Answer
Answer: B. Collecting data automatically from websites using software
Explanation: Web Scraping is the automated process of extracting information from web pages using specialized software or scripts.
Q27. During data acquisition, collecting data from a website without the owner's permission may be:
A. Encouraged
B. Illegal or unethical
C. Mandatory
D. Always free to use
Show Answer
Answer: B. Illegal or unethical
Explanation: Data should always be collected legally and ethically. Using copyrighted or restricted data without permission may violate laws or website policies.
Q28. Which platform is widely used by data scientists to share datasets and machine learning projects?
A. Microsoft Word
B. WhatsApp
C. Kaggle
D. Paint
Show Answer
Answer: C. Kaggle
Explanation: Kaggle is a popular online platform where users can access datasets, participate in competitions, and share machine learning projects.
Q29. Government portals that provide open datasets generally use which domain?
A. .com
B. .gov
C. .net
D. .edu
Show Answer
Answer: B. .gov
Explanation: Government websites usually use the .gov domain and often provide authentic public datasets for research and analysis.
Q30. Google Dataset Search is mainly used to:
A. Edit datasets
B. Search and discover datasets available on the internet
C. Build AI models
D. Create spreadsheets
Show Answer
Answer: B. Search and discover datasets available on the internet
Explanation: Google Dataset Search is a specialized search engine that helps users locate publicly available datasets from various sources.
Q31. What type of data includes reviews, opinions, feelings, and emotions?
A. Numeric Data
B. Quantitative Data
C. Textual (Qualitative) Data
D. Continuous Data
Show Answer
Answer: C. Textual (Qualitative) Data
Explanation: Textual or Qualitative Data describes qualities, opinions, emotions, and characteristics that cannot be measured using numbers.
Q32. Numeric data that can take any value within a given range, such as height or weight, is called:
A. Discrete Data
B. Continuous Data
C. Qualitative Data
D. Raw Data
Show Answer
Answer: B. Continuous Data
Explanation: Continuous Data can have an infinite number of values within a range, such as height, weight, temperature, and distance.
Q33. Which type of data consists of countable whole numbers such as the number of students in a class?
A. Continuous Data
B. Discrete Data
C. Qualitative Data
D. Textual Data
Show Answer
Answer: B. Discrete Data
Explanation: Discrete Data represents countable values that cannot be divided into fractions, such as the number of books or students.
Q34. Data Features are the ________ or properties of the data.
A. Sources
B. Characteristics
C. Outputs
D. Algorithms
Show Answer
Answer: B. Characteristics
Explanation: Data Features are the characteristics or attributes of a dataset, such as age, marks, salary, or temperature.
Q35. In an AI model, the input variables used to make predictions are called:
A. Dependent Features
B. Independent Features
C. Output Features
D. Testing Features
Show Answer
Answer: B. Independent Features
Explanation: Independent Features are the input values provided to the AI model. These variables help predict the dependent feature.
Q36. The value that an AI model tries to predict is known as the:
A. Independent Feature
B. Input Feature
C. Dependent Feature
D. Hidden Feature
Show Answer
Answer: C. Dependent Feature
Explanation: The Dependent Feature is the target or output that the AI model predicts using the independent features.
Q37. Clean Data is data that is free from:
A. Numbers
B. Text
C. Duplicate records, missing values, and outliers
D. Tables
Show Answer
Answer: C. Duplicate records, missing values, and outliers
Explanation: Clean Data contains accurate, complete, and consistent information without unnecessary duplicates, errors, or missing values.
Q38. Which quality of data indicates how closely the data matches real-world values?
A. Structure
B. Cleanliness
C. Accuracy
D. Availability
Show Answer
Answer: C. Accuracy
Explanation: Accuracy means that the data correctly represents real-world facts and contains minimal errors.
Q39. Kaggle assigns a "Usability Score" to datasets based on:
A. The file size
B. The number of downloads only
C. Ratings and feedback from users
D. The programming language used
Show Answer
Answer: C. Ratings and feedback from users
Explanation: The Usability Score helps users identify datasets that are well-organized, properly documented, and useful for machine learning projects.
Q40. Information that is accurate, complete, consistent, and well-structured is known as:
A. Bad Data
B. Good Data
C. Raw Data
D. Continuous Data
Show Answer
Answer: B. Good Data
Explanation: Good Data is reliable, accurate, complete, and organized, making it suitable for analysis and AI model development.
Q41. What is Data Processing?
A. Collecting data from different sources
B. Manipulating raw data to produce meaningful information
C. Storing data permanently
D. Deleting unwanted files
Show Answer
Answer: B. Manipulating raw data to produce meaningful information
Explanation: Data Processing is the process of organizing, cleaning, and transforming raw data into meaningful information that can be analyzed and used for decision-making.
Q42. The process of making sense of processed data to draw useful conclusions is called:
A. Data Presentation
B. Data Interpretation
C. Data Acquisition
D. Data Storage
Show Answer
Answer: B. Data Interpretation
Explanation: Data Interpretation involves analyzing processed data to identify patterns, trends, and conclusions that support informed decision-making.
Q43. Quantitative Data Interpretation mainly answers questions such as:
A. Why do people feel happy?
B. How many and how often?
C. What is the meaning of life?
D. Which movie is the best?
Show Answer
Answer: B. How many and how often?
Explanation: Quantitative Data Interpretation deals with numerical data and helps answer measurable questions like "How many?", "How much?", and "How often?".
Q44. Which method of data interpretation presents information in rows and columns?
A. Graphical Representation
B. Textual Representation
C. Tabular Representation
D. Audio Representation
Show Answer
Answer: C. Tabular Representation
Explanation: Tabular Representation organizes data into rows and columns, making it easy to compare values and analyze information.
Q45. Which type of chart represents data as slices of a circle to show proportions?
A. Line Graph
B. Bar Graph
C. Pie Chart
D. Histogram
Show Answer
Answer: C. Pie Chart
Explanation: A Pie Chart displays the contribution of each category as a part of the whole, making comparisons easy.
Q46. Data Visualization helps users to:
A. Increase internet speed
B. Understand patterns and trends more easily
C. Create programming languages
D. Delete unnecessary data automatically
Show Answer
Answer: B. Understand patterns and trends more easily
Explanation: Charts, graphs, and dashboards make complex datasets easier to understand and help identify trends and relationships quickly.
Q47. Which software is widely used for creating interactive dashboards and visualizing data?
A. Microsoft Paint
B. Tableau
C. VLC Media Player
D. Notepad
Show Answer
Answer: B. Tableau
Explanation: Tableau is a powerful data visualization tool that helps users analyze data and create interactive charts, graphs, and dashboards.
Q48. Identifying the most popular music genre from a collected dataset is an example of:
A. Data Generation
B. Data Security
C. Data Interpretation
D. Data Acquisition
Show Answer
Answer: C. Data Interpretation
Explanation: Finding trends or drawing conclusions from collected data is known as Data Interpretation.
Q49. Longitudinal studies are conducted over a ________ period of time.
A. Very short
B. Considerable
C. Random
D. Fixed one-day
Show Answer
Answer: B. Considerable
Explanation: Longitudinal studies collect data over an extended period to observe changes, patterns, and trends over time.
Q50. During which stage of the AI Project Cycle is Tableau most useful?
A. Problem Scoping
B. Data Acquisition
C. Data Exploration
D. Deployment
Show Answer
Answer: C. Data Exploration
Explanation: Tableau is mainly used during the Data Exploration stage to visualize data, discover patterns, identify trends, and gain meaningful insights before building an AI model.
❓ Quick Revision
- Data Literacy is the ability to read, understand, interpret, analyze, and communicate data.
- The Data Pyramid (DIKW) consists of Data → Information → Knowledge → Wisdom.
- Data Privacy controls how personal data is collected and used, while Data Security protects it from unauthorized access.
- Important ethical principles include Consent, Transparency, Accountability, and Anonymity.
- Data can be collected through Primary Sources (surveys, interviews, observations) and Secondary Sources (Kaggle, government portals).
- Data Discovery searches for existing datasets, while Data Generation creates new data using experiments or sensors.
- Independent Features are inputs to an AI model, whereas Dependent Features are the outputs to be predicted.
- Good data should be accurate, complete, consistent, clean, and well-structured.
- Tableau is used for Data Visualization during the Data Exploration stage of the AI Project Cycle.
? Exam Tip
For CBSE Class 9 AI examinations, remember the DIKW Data Pyramid, the difference between Data Privacy and Data Security, Primary vs Secondary Data Sources, Independent vs Dependent Features, and the role of Tableau in Data Exploration. These topics are frequently asked in MCQs, competency-based, and case-study questions.