Class 9 Computer Science MCQs: Data And Analysis

MCQs (sample)

Showing 25 questions from this chapter. For a full timed test, use “Start online test”.

1. 1. What are the two main types of data in data science?

   • Qualitative and Quantitative
   • Ordinal and Nominal
   • Discrete and Continuous
   • Primary and Secondary
   Answer & explanation

   Correct: Qualitative and Quantitative

   Data in science is classified into qualitative (categorical) and quantitative (numeric).

2. 2. What does the 'Volume' in the three Vs of big data refer to?

   • The amount of data
   • The speed of data
   • The variety of data formats
   • The quality of data
   Answer & explanation

   Correct: The amount of data

   Volume refers to the amount of data, indicating how much data is being dealt with.

3. 3. What is data analytics primarily used for?

   • To examine raw data and draw conclusions
   • To create computer software
   • To enhance network security
   • To develop new programming languages
   Answer & explanation

   Correct: To examine raw data and draw conclusions

   Data analytics is the process of examining raw data to draw conclusions from it.

4. 4. Which type of data can be represented in numerical form?

   • Qualitative Data
   • Quantitative Data
   • Nominal Data
   • Ordinal Data
   Answer & explanation

   Correct: Quantitative Data

   Quantitative data is numeric and can be computed mathematically.

5. 5. Which of the following is NOT one of the three Vs of big data?

   • Volume
   • Velocity
   • Validation
   • Variety
   Answer & explanation

   Correct: Validation

   Validation is not one of the three Vs; the three Vs are Volume, Velocity, and Variety.

6. 6. Which of the following is NOT a technique used in data analytics?

   • Statistical techniques
   • Mathematical calculations
   • Web development
   • Charts
   Answer & explanation

   Correct: Web development

   Web development is not a technique used in data analytics; the other options are techniques for analyzing data.

7. 7. What is an example of Ordinal Data?

   • Colors
   • Economic Status
   • Gender
   • Transportation Type
   Answer & explanation

   Correct: Economic Status

   Ordinal data has a specific order or ranking, such as economic status.

8. 8. What year did the term 'big data' emerge?

   • 1995
   • 2000
   • 2000s
   • 2010
   Answer & explanation

   Correct: 2000s

   The term 'big data' emerged in the early 2000s.

9. 9. What does Data Science primarily utilize for analyzing data?

   • Color theory
   • Mathematics and statistics
   • Social media marketing
   • Graphic design
   Answer & explanation

   Correct: Mathematics and statistics

   Data Science uses mathematics, statistics, and data analysis to gain insights from data.

10. 10. Nominal data can be best described as:

    • Data with a specific order.
    • Data that can be counted.
    • Data with mutually exclusive categories.
    • Data that has a true zero point.
    Answer & explanation

    Correct: Data with mutually exclusive categories.

    Nominal data consists of categories without a specific order.

11. 11. What is the purpose of Hadoop?

    • Visualize data
    • Store and analyze big datasets
    • Manage data security
    • Perform statistical analysis
    Answer & explanation

    Correct: Store and analyze big datasets

    Hadoop is developed specifically to store and analyze big datasets.

12. 12. Which component of data science focuses on discovering patterns in datasets?

    • Deep Learning
    • Statistics
    • Data Mining
    • Big Data
    Answer & explanation

    Correct: Data Mining

    Data Mining is a subset of data science that focuses on discovering patterns and relationships in existing datasets.

13. 13. Which of the following is an example of Discrete Data?

    • Height
    • Number of students in a class
    • Temperature
    • Weight of a newborn baby
    Answer & explanation

    Correct: Number of students in a class

    Discrete data can only take certain values and can be counted, like the number of students.

14. 14. How does big data help in product development?

    • By maintaining data security
    • By analyzing customer needs
    • By limiting product testing
    • By supporting traditional data formats
    Answer & explanation

    Correct: By analyzing customer needs

    Big data helps develop products by analyzing customer needs and wants.

15. 15. What is 'Big Data'?

    • A small amount of data
    • Data that is easy to analyze
    • Handling large volumes of data
    • Data that is only textual
    Answer & explanation

    Correct: Handling large volumes of data

    Big Data refers to handling large volumes of data which helps in finding patterns and trends.

16. 16. Continuous Data is best defined as:

    • Data that can only take certain finite values.
    • Data that can be measured between two points.
    • Data represented in categories without order.
    • Data with unique identifiers.
    Answer & explanation

    Correct: Data that can be measured between two points.

    Continuous data has an unspecified number of measurements possible between two realistic points.

17. 17. What does 'Velocity' in big data indicate?

    • The amount of data
    • The cost of data storage
    • The speed of data reception
    • The security of data
    Answer & explanation

    Correct: The speed of data reception

    Velocity refers to the speed of data, specifically how quickly it is received.

18. 18. What is the goal of data analytics?

    • To create software solutions
    • To transform raw data into actionable knowledge
    • To enhance customer service directly
    • To improve team communication
    Answer & explanation

    Correct: To transform raw data into actionable knowledge

    The goal of data analytics is to transform raw data into actionable knowledge that can inform decision-making.

19. 19. What differentiates Ratio scaled data from Interval scaled data?

    • Interval data has no true zero point.
    • Both have the same characteristics.
    • Ratio data is nominal.
    • Interval data can be counted.
    Answer & explanation

    Correct: Interval data has no true zero point.

    Ratio scaled data has meaningful differences and a true zero point, while interval scaled data does not.

20. 20. Which challenge of big data relates to managing data integrity?

    • Data Quality
    • Data Security and privacy
    • Rapid growth of data
    • Data integration
    Answer & explanation

    Correct: Data Quality

    Data Quality refers to the issues arising from poor quality data affecting insights.

21. 21. Which term refers to the ability of computers to understand human language?

    • Predictive Analysis
    • Data Visualization
    • Natural Language Processing (NLP)
    • Machine Learning
    Answer & explanation

    Correct: Natural Language Processing (NLP)

    Natural Language Processing (NLP) is the ability of computers to interpret and generate human language.

22. 22. Primary data is collected through which method?

    • Past research studies
    • Surveys and Questionnaires
    • Online databases
    • Government records
    Answer & explanation

    Correct: Surveys and Questionnaires

    Primary data is collected directly from the source, such as through surveys.

23. 23. In which sector does big data NOT have applications listed in the content?

    • Healthcare
    • Sports
    • Manufacturing
    • Government
    Answer & explanation

    Correct: Sports

    Sports is not mentioned as a sector where big data has applications.

24. 24. Which of the following is an example of a business problem that data science can solve?

    • Creating new programming languages
    • Deciding best routes for shipping.
    • Enhancing user interface design
    • Improving office decor
    Answer & explanation

    Correct: Deciding best routes for shipping.

    Deciding the best routes for shipping is a business problem that data science can help solve through data analysis.

25. 25. Which of the following is categorized as Secondary data collection?

    • Interviews
    • Surveys and Questionnaires
    • Published sources
    • Experiments
    Answer & explanation

    Correct: Published sources

    Secondary data is collected from previously recorded sources, such as published material.