MCQ

Class 10 computer chapter 5 MCQs with answers pdf | DSLC

Class 10 computer chapter 5 MCQ with answers PDF covering the Data Science Life Cycle (DSLC) is available for students preparing for Punjab Boards. This chapter includes important concepts such as data collection, data validation, data analysis, data interpretation, data visualization, and databases. Students can use these Class 10 Computer Chapter 5 MCQs with answers for exam preparation, revision, and online MCQ practice.

10CSE Chapter 5 5.2 Overview of the Data Science Life Cycle

5.2 Overview of the Data Science Life Cycle

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Using dropdowns or checkboxes in surveys helps to:

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Importance to setting clear objective:

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Final step of DSLC method:

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Blank cells, such as no sport name or study time of day, are examples of:

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How many types of common Data Errors?

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When selecting a data source, you should ask:

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Which method is used to find meaning from data?

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Total number of steps in DSLC:

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To avoid bias, we should:

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Share the results is called:

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To find out which sports students enjoy, we can create a survey with questions such as:

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Which allow software to collect data from websites or applications?

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A good problem is one that can be answered by:

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Data is like raw material, and we must gather the right kind of data before we can:

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When we refine a problem, we:

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Data Science life cycle is helpful in:

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Analyzing data helps us make decisions based on:

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Clean data leads to smart decisions, whereas dirty data leads to:

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DSLC stands for:

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Raw data is the original information we collect from people, sensors, websites, or apps that:

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tool help to validate data:

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Raw data is often:

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Next step after Problem identification:

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Standardizing formats means changing entries like "CRICKET" to:

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Redundancy handling is done in:

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Find trends & patterns involved in:

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If we only survey boys about their favorite sports, the results will be:

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Data only shows part of truth and miss the full picture:

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Which of the following is the best tool for conduct online survey?

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Making a clear target to solve a problem is referred to:

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After data cleaning next step is:

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Which of the following is used as a tool for Analysis?

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IoT devices like smart watches or temperature sensors are useful in:

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Data Validation is important for:

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How many type of Data validation techniques are there?

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Data which has not been checked or cleaned:

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Problem understanding means:

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Writing your objectives like a checklist helps to:

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Public data collection method is:

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Which of the following allow user to focus on Project?

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Method in which we asked question and record answers:

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"Frequency = 1000 times/week" in a student survey is an example of:

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IoT is useful in:

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Computer Science and Entrepreneurship 10th Class New Syllabus 2026 MCQs with Answers

 

Chapter 5 Data Science
[Tech ICT Group (Chapter 4) and Simple Computer Science Group]

5.1 Introduction to Data Science

5.2 Overview of the Data Science Life Cycle

5.3 Tools for Visualization

5.4 Databases and Storing Data

Complete Exercise Solution

Complete Chapter MCQs

 

Select other Chapter from Class 10 Computer Science & Entrepreneurship 2026 

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