Unit 2 Data Literacy Class 9 AI Question Answers
Unit 2 Data Literacy Class 9 AI Question Answers
Revision Time:
Q1. Cultivating Data Literacy means:
a) Utilize vocabulary and analytical skills
b) Acquire, develop, and improve data literacy skills
c) Develop skills in statistical methodologies
d) Develop skills in Math
Q2. Data Privacy and Data Security are often used interchangeably but they are different from each other
a) True
b) False
Q3. The _______________ provides guidance on using data efficiently and with all levels of awareness.
a) data security framework
b) data literacy framework
c) data privacy framework
d) data acquisition framework
Q4. __________________ allows us to understand why things are happening in a particular way.
a) data
b) information
c) knowledge
d) wisdom
Q5. _______________________ is the practice of protecting digital information from unauthorized access, corruption, or theft throughout its entire lifecycle.
a) data security
b) data literacy
c) data privacy
d) data acquisition
Unit 2 Data Literacy Class 9 AI Question Answers
Q6. What are the basic building blocks of qualitative data?
a. Individuals
b. Units
c. Categories
d. Measurements
Q7. Which among these is not a type of data interpretation?
a. Textual
b. Tabular
c. Graphical
d. Raw data
Q8. Quantitative data is numerical in nature.
a. True
b. False
Q9. A Bar Graph is an example of?
a. Textual
b. Tabular
c. Graphical
d. None of the above
Q10. _____________________relates to the manipulation of data to produce meaningful insights.
a. Data Processing
b. Data Interpretation
c. Data Analysis
d. Data Presentation
Unit 2 Data Literacy Class 9 AI Question Answers
Q11. At which stage of the AI project cycle does Tableau software prove useful?
Q12. Name any five graphs that can be made using Tableau software
Q13. In the below excel sheet-
A) Is the Year qualitative or quantitative?
B) Is Song Length discrete or continuous?
C) Is the Genre discrete or continuous?
Q14. What is the importance of data visualization?
Unit 2 Data Literacy Class 9 AI Question Answers
Extra Questions
Unit 2 Data Literacy Class 9 AI Question Answers
Q1. What do you mean by Data Literacy?
Q2. What do you mean by Data and Information?
Q3. What do you mean by Data Privacy?
Q4. What are the best practices that can help us to ensure data privacy?
● Understanding what data, we have collected, how it is handled, and where it is stored.
● Necessary data required for a project should only be collected.
● User consent while data collection must be of utmost importance.
Q5. What do you mean by Data Security. Why it is important?
Data Security is important because of the following reasons.
Unit 2 Data Literacy Class 9 AI Question Answers
Q6. Define cyber security.
Q7. What are the best practices that can be done to enhance cyber security?
Q8. Differentiate between Quantitative and Qualitative data.
Numeric Data (Quantitative Data) Textual Data (Qualitative Data) It is made up of numbers It is made up of words and phrases It is used for Statistical Data It is used for Natural Language Processing (NLP) Any measurements, readings, or values would count as numeric data. for example: Cricket Score, Restaurant Bill Search queries on the internet are an example
of textual data. for example: “Which is a good park nearby?”
Q9. Name the three domains of AI and also name the types of Data used in each domain of AI.
Domain Name Type of Data Computer Vision(CV) Visual data for eg. images, videos Natural Language Processing(NLP) Textual data for eg. Documents, pdf files Statistical Data(SD) Numeric Data for eg. Tables, Excel Sheets
Q10. Explain Data acquisition along with three key steps involved.
Data Acquisition typically comprises three key steps: 1. Data Discovery: In this step we search for new datasets. 2. Data Augmentation: In this step we generate a new data by adding more data to the existing data. 3. Data Generation: In this step we generate new data if data is not available.
searching for datasets suitable for training AI models.
Unit 2 Data Literacy Class 9 AI Question Answers
Q11. What are the factors that make data good or bad?
Factors that make bad data are:
Q12. What are the two sources for Acquiring Data in AI models?
Primary Data Sources — Some of the sources for primary data include surveys, interviews, experiments, etc. The data generated from the experiment is an example of primary data. Secondary Data Sources—Secondary data collection obtains information from external sources, rather than generating it personally. Some sources for secondary data collection include Kaggle, , UCI etc
Q13. What is Web Scraping?
Q14. Name the key ethical concerns that should be taken care during data acquisition?
Q15. Briefly explain the three primary factors that determine the usability of data.
1. Structure: It defines how data is stored. Data stored in spreadsheet is more structured rather than data stored in Text document. 2. Cleanliness: Clean data is free from duplicates, missing values, outliers, and other anomalies that may affect its reliability and usefulness for analysis 3. Accuracy: Accuracy indicates how well the data matches real-world values, ensuring reliability. Accurate data closely reflects actual values without errors, enhancing the quality and trustworthiness of the dataset.
Unit 2 Data Literacy Class 9 AI Question Answers
Q16. What do you mean by Data features? Explain with example.
Q17. Differentiate between the two types of Data features in AI models.
Independent features are the input to the model, they’re the information we provide to make predictions. Dependent features, on the other hand, are the outputs or results of the model.
Q18. Is Data Processing and Data Interpretation is same?
Q19. What do you mean by Data processing and Data interpretation?
Data Interpretation refers to analyzing data to arrive at meaningful decisions. It is the process of making sense out of data that has been processed. It helps us to answer critical questions using data.
Q20. Name and explain two types of Data Interpretation.
1. Qualitative Data Interpretation: Qualitative data tells us about the emotions and feelings of people. It is focused on insights and motivations of people. 2. Quantitative Data Interpretation: Quantitative data interpretation is made on numerical data. It helps us answer questions like “when,” “how many,” and “how often”. For example – (how many) numbers of likes on the Instagram post.
Unit 2 Data Literacy Class 9 AI Question Answers
Q21. Write all the five Steps to Qualitative Data Analysis.
Q22. What are the primary data collecting methods used for interpreting qualitative data? Name any five
Q23. What are the primary data collecting methods used for interpreting quantitative data? Name any five
Q24. Write all the four Steps to Quantitative Data Analysis.
Q25. Differentiate between Qualitative & Quantitative Data Interpretation.
Qualitative Data Interpretation Quantitative Data Interpretation Provides insights into feelings and emotions Provides insights into quantity Question starts with ‘how’ and ‘why’ Question starts with ‘when’, ‘how many’ or ‘how often’ Methods – Interviews, Focus Groups Methods – Assessment, Tests, Polls, Surveys Example question – Why do students like attending online classes? Example question – How many students
like attending online classes?
Unit 2 Data Literacy Class 9 AI Question Answers
Q26. What are the three types of Data Interpretation? Explain in brief.
1. Textual Data Interpretation: In this data is mentioned in the text form, usually in a paragraph. It is used when the data is not large and can be easily comprehended by reading. It is not suitable for large data. 2. Tabular Data Interpretation: Data is represented systematically in the form of rows and columns. It is easy to compare values and find pattern. 3. Graphical Data Interpretation: Visual tools like bar charts, pie charts, line graphs, histograms are used in this to communicate data.
Q27. Name the software which make it easier for us to present data.
Important Links
Class IX A.I. Book
Class IX AI Curriculum
Class X AI Book
Class X AI Curriculum 2025-26
Python Manual
A.I. Reflection Project Cycle and Ethics Class 9 Notes Important Points
A.I. Reflection Project Cycle and Ethics Class 9 MCQ
A.I. Reflection Project Cycle and Ethics Class 9 Question Answers
Unit 2 – Data Literacy NOTES Important Points
Unit 2 – Data Literacy MCQ
Unit 2 Data Literacy Class 9 AI Question Answers
Unit 2 Data Literacy Class 9 AI Question Answers
v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v