9th Chapter

9th Computer Science English Medium Chapter 9 Test

Matric 9th Class Computer Science Unit 9 MCQ Test with Answers – SSC Part 1 Online Practice

9th Computer Science English Medium Chapter 9 MCQ's Test

Start Chapter 9 Test

Matric 9th Class Computer Science Unit 9 MCQ Test with Answers – SSC Part 1 Online Practice

Sr. # Questions Answers Choice
1 ------------- is a method of collecting information from individuals.
  • A. Data Finding
  • B. Data hiding
  • C. Survey
  • D. Data visualization
2 How does data sciecne add value to bing data.
  • A. By creating more data
  • B. By extracting insights and predictions from data
  • C. By making data storage more efficient
  • D. By ensuring data quality and consistency
3 What is the types of data is used to categorize items without implying any order.
  • A. Ordinal data
  • B. Discrete Data
  • C. Nominal Data
  • D. Continous Data
4 Which tool can be used to create surveys online?
  • A. Microsof word
  • B. Excel spreadsheets
  • C. Adobe Photoshop
  • D. Google forms
5 Which of the following is not one of the characteristics of bign data.
  • A. Veracity
  • B. Validity
  • C. Volume
  • D. Velocity
6 What is data
  • A. Processed information
  • B. A list of observed events
  • C. A collectionof numebrs only
  • D. Raw facts gathered about things
7 What is the role of domain knowledge in data sciecne.
  • A. writing code for data analysis
  • B. Visualizing data
  • C. Understanding the specific context of data
  • D. conducting staticial tests
8 Which of the following is an example of interval scaled attribute.
  • A. Age
  • B. Weight
  • C. Temperature in Celsius
  • D. Hight
9 -------------- is the grahical represnetation of data through use of common charts, plots, infographics and animations.
  • A. Data cleaning
  • B. Missing values
  • C. Data visualization
  • D. Data hiding
10 Which of the following key concepts involves transforming raw data into a structured format that is suitable fof analyis.
  • A. Data ethics
  • B. Data modeling
  • C. Data exploration
  • D. Data collection

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