Artificial Intelligence

CBSE Class 9 Artificial Intelligence (402) Unit 2 – Data Literacy Important Subjective Questions (2, 3 & 4 Marks) with Answers

Class 9 · Artificial Intelligence

CBSE Class 9 Artificial Intelligence (402)

Unit 2 – Data Literacy

These important subjective questions are prepared according to the latest CBSE competency-based examination pattern. The questions are based entirely on the Class 9 Artificial Intelligence Facilitator Handbook and include competency-based, application-based, case-study and Higher Order Thinking Skills (HOTS) questions.

Instructions

Total Questions : 25
This section contains 10 questions of 2 marks each.
Read each question carefully before answering.
Support your answers with suitable examples wherever possible.

Section A – 2 Mark Questions

Q1. Define Data Literacy. Mention any two benefits of becoming data literate.

Answer:

Data Literacy is the ability to understand, interpret and communicate with data so that meaningful decisions can be made.

Benefits:

Helps in making informed decisions.
Develops critical thinking and problem-solving skills.

Example: A student compares reviews and ratings before purchasing an online course instead of selecting it randomly.

Q2. Explain the four stages of the Data Pyramid with the help of the Traffic Light example.

Answer:

Stage	Traffic Light Example
Data	Red, Traffic_Light_1
Information	The traffic light has turned red.
Knowledge	The signal in my direction is red.
Wisdom	I should stop my car.

Q3. Differentiate between Data Privacy and Data Security.

Answer:

Data Privacy	Data Security
Controls how data is collected and shared.	Protects data from unauthorized access.
Focuses on proper use of personal information.	Focuses on protecting information from cyber attacks.
Example: User Consent.	Example: Passwords and Encryption.

Q4. Mention any four steps of the Data Literacy Process Framework.

Answer:

Plan
Communicate
Assess
Develop Culture
Prescriptive Learning
Evaluate

(Any four)

Q5. State any two best practices for Cyber Security.

Answer:

Use strong and unique passwords.
Enable Two-Factor Authentication (2FA).
Use websites with HTTPS.
Keep operating system and antivirus updated.

(Any two)

Q6. Explain any two situations in which Data Privacy may be compromised.

Answer:

Installing unverified mobile applications.
Accepting Terms and Conditions without reading them.

These activities may expose personal information to unauthorized users.

Q7. Differentiate between Primary Data Sources and Secondary Data Sources with one example each.

Answer:

Primary Data	Secondary Data
Collected directly by the researcher.	Collected by someone else earlier.
Survey conducted by a school.	Kaggle Dataset or data.gov.in

Q8. A student wants to download a dataset for an AI project.

Suggest any two reliable sources from where the student can obtain the data.

Answer:

Kaggle
Google Dataset Search
Government Open Data Portal (data.gov.in)

(Any two)

Q9. Differentiate between Continuous Data and Discrete Data with suitable examples.

Answer:

Continuous Data	Discrete Data
Can take any value within a range.	Contains only whole numbers.
Height, Weight, Temperature.	Number of students, Number of books.

Q10. Why is Data Preprocessing important before training an AI model?

Answer:

Data preprocessing improves the quality of data before it is used by an AI model.

It includes:

Removing duplicate records.
Handling missing values.
Cleaning incorrect information.
Making the data uniform.

Good quality data improves the accuracy and reliability of AI predictions.

Section B – 3 Mark Questions

Q11. (Competency Based)

A student wants to purchase a laptop for online learning. Instead of buying the first laptop he sees, he compares prices, customer ratings, technical specifications and reviews from different websites.

Answer the following:

How is the student demonstrating Data Literacy?
Mention any two benefits of this approach.
What kind of decision is he making?

Answer:

(i) The student is analysing available data before making a decision. This shows that he is data literate.

(ii) Benefits:

Helps select the best product.
Prevents unnecessary spending.

(iii) He is making an informed decision based on evidence instead of assumptions.

Q12. (Case Study)

A hospital is developing an AI system to predict diseases. The developers collect patients' age, medical history, blood test reports and X-ray images before training the AI model.

Answer the following:

Name any three types of data collected.
Why is Data Preprocessing necessary?
Mention one ethical practice that should be followed while collecting patient data.

Answer:

(i) Types of Data

Numeric Data (Age, Blood Test Results)
Textual Data (Medical History)
Visual Data (X-ray Images)

(ii)

Data preprocessing removes duplicate, incomplete and incorrect records, making the data suitable for AI training.

(iii)

The hospital should obtain proper patient consent before collecting or using personal medical information.

Q13. Explain the three methods of acquiring data with suitable examples.

Answer:

Method	Description	Example
Data Discovery	Searching and downloading existing datasets.	Downloading road images from an open dataset.
Data Augmentation	Increasing data by modifying existing data.	Changing image brightness or rotation.
Data Generation	Creating completely new data.	Collecting temperature readings using sensors.

Q14. (Application Based)

A school is conducting an AI project to predict students' examination performance.

Identify any three important data features that can be collected for this project and explain why these features are useful.

Answer:

Possible data features include:

Attendance Percentage
Assignment Marks
Unit Test Scores

These features help the AI identify patterns between students' academic performance and their study habits.

Q15. (Competency Based)

A school survey records the following information:

Name
Age
Study Hours
Final Result (Pass/Fail)

Identify the Independent Features and the Dependent Feature.

Answer:

Independent Features:

Name
Age
Study Hours

Dependent Feature:

Final Result (Pass/Fail)

The independent features help the AI predict the dependent feature.

Q16. (HOTS)

Explain why Data Interpretation is important before making decisions. Support your answer with any three suitable points.

Answer:

Helps in making informed decisions.
Identifies trends and hidden patterns.
Reduces cost by identifying actual requirements.

Example:

A restaurant analyses customer reviews and removes unpopular dishes, reducing food wastage and improving customer satisfaction.

Q17. (Case Study)

A city administration wants to analyse traffic congestion using data collected from traffic cameras and GPS devices.

Answer the following:

Name two sources of data.
Suggest one graphical method for presenting the results.
Why is graphical representation preferred over raw tables?

Answer:

(i) Sources of Data

Traffic Cameras
GPS Devices

(ii)

Bar Graph or Line Graph.

(iii)

Graphs make trends, comparisons and patterns easier to understand than raw numerical tables.

Q18. (Competency Based)

A student has collected examination marks of 500 students in an Excel sheet. The teacher asks him to create a report showing the highest marks, average marks and subject-wise comparison using graphs.

Answer the following:

Name one suitable software tool.
Which presentation format should be used?
Why is visualization useful in this situation?

Answer:

(i) MS Excel or Tableau.

(ii) Graphical Presentation (Bar Graph or Line Graph).

(iii)

Visualization helps users quickly identify subject-wise performance, compare results and understand overall trends without analysing hundreds of numerical values manually.

Section C – 4 Mark Questions

Q19. (Case Study Based)

A school plans to develop an AI system to identify students who require additional academic support. The school collects attendance records, unit test marks, assignment submissions and classroom participation data before training the AI model.

Answer the following:

Identify the types of data collected.
Explain why Data Preprocessing is necessary before training the AI model.
State one ethical practice that must be followed while collecting student data.
Suggest one graphical method to present the final analysis.

Answer:

(i) Types of Data

Numeric Data – Attendance percentage and marks.
Textual Data – Student names and assignment remarks.

(ii) Data Preprocessing

Removes duplicate records.
Corrects missing or incorrect values.
Makes the dataset uniform.
Improves AI prediction accuracy.

(iii) Ethical Practice

The school should obtain consent before collecting personal information and ensure student data remains confidential.

(iv) Graphical Method

A Bar Graph or Line Graph can be used to compare students' academic performance.

Q20. Explain the complete process of acquiring data for an AI project. Mention the ethical practices that should be followed while collecting data.

Answer:

The process of acquiring data consists of the following steps:

Data Discovery – Searching and downloading existing datasets.
Data Augmentation – Increasing available data by modifying existing data.
Data Generation – Creating new data using surveys, sensors or experiments.

Ethical Practices

Collect data only after obtaining user consent.
Maintain transparency about how the data will be used.
Protect the identity of users (Anonymity).
Avoid bias while collecting data.

Following these practices ensures that AI systems are reliable, fair and trustworthy.

Q21. (Competency Based)

A city administration wants to analyse traffic congestion using GPS devices, CCTV cameras and weather reports. The collected information is used to create an interactive dashboard for traffic management officers.

Answer the following:

Name any three sources of data used in this project.
Which stage of AI mainly uses Data Visualization?
Suggest two charts suitable for presenting traffic trends.
How will visualization help traffic management officers?

Answer:

(i) Sources of Data

GPS Devices
CCTV Cameras
Weather Reports

(ii)

Data Exploration stage.

(iii)

Line Graph
Bar Graph

(iv)

Visualization allows officers to quickly identify traffic patterns, compare congestion levels and make faster decisions regarding traffic control.

Q22. (HOTS)

A hospital is planning to build an AI model that predicts diseases using patient records collected over the last five years.

Discuss the importance of Data Interpretation in this project by explaining any four points.

Answer:

Helps doctors make informed medical decisions.
Identifies hidden disease patterns.
Improves treatment planning.
Reduces healthcare cost by identifying high-risk patients early.

Without proper interpretation, even a large amount of data cannot provide useful insights.

Q23. (Application Based)

Differentiate between Qualitative and Quantitative methods of Data Interpretation. Also explain the three common presentation formats used to present data.

Answer:

Qualitative Method	Quantitative Method
Focuses on opinions, feelings and behaviour.	Focuses on numerical values and measurable information.
Examples: Interviews, Observations, Focus Groups.	Examples: Surveys, Polls and Tests.

Presentation Formats

Textual Presentation – Information presented in paragraph form.
Tabular Presentation – Data organised into rows and columns.
Graphical Presentation – Data shown using graphs and charts.

Q24. (Case Study Based)

A music company wants to identify the most popular music genre among teenagers. The company collects data from streaming platforms and creates an interactive dashboard using Tableau.

Answer the following:

Name the no-code software used.
Which chart can be used to compare different music genres?
Why is Data Visualization better than raw numerical tables?
State one advantage of using an interactive dashboard.

Answer:

(i) Tableau Public.

(ii) Bar Chart.

(iii)

Visualization helps users understand trends, patterns and comparisons much faster than reading large tables.

(iv)

Interactive dashboards allow users to analyse data dynamically by applying filters and exploring different perspectives.

Q25. (Integrated Competency Question)

Your school wants to develop a Student Performance Dashboard using MS Excel and Tableau. Teachers collect attendance, examination marks, assignment scores and participation records throughout the year.

Answer the following:

Identify the independent and dependent features.
Explain why Data Cleaning should be performed before creating the dashboard.
Name any two software tools that can be used for visualization.
State any two advantages of Data Visualization in education.

Answer:

(i) Independent Features

Attendance
Assignment Scores
Participation

Dependent Feature

Final Examination Result

(ii)

Data Cleaning removes duplicate records, fills missing values and ensures consistency before visualization.

(iii) Software Tools

Tableau Public
MS Excel
Datawrapper

(iv) Advantages

Helps teachers identify learning trends quickly.
Makes comparison and analysis easier.
Supports informed academic decisions.
Improves presentation of information.

Revision Tips

Understand the complete Data Pyramid (Data → Information → Knowledge → Wisdom).
Learn all six stages of the Data Literacy Process Framework.
Revise the difference between Data Privacy and Data Security.
Remember the Cyber Security Do's and Don'ts.
Differentiate between Primary and Secondary Data Sources.
Understand Continuous, Discrete, Textual and Visual Data with examples.
Learn the concepts of Data Discovery, Data Augmentation and Data Generation.
Practice Independent and Dependent Features.
Remember the importance of Data Cleaning before AI training.
Know the advantages of Data Interpretation and Data Visualization.
Revise Bar Chart, Pie Chart and Line Graph.
Learn the use of Tableau, MS Excel and Datawrapper for creating dashboards.

★★★★★ End of Class 9 AI Unit 2 Subjective Question Bank with Answers ★★★★★

CBSE Class 9 Artificial Intelligence (402) Unit 2 – Data Literacy Important Subjective Questions (2, 3 & 4 Marks) with Answers