Class 10 computer chapter 5 MCQs with answers pdf | DSLC

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

Raw data is often:

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

Data Science life cycle is helpful in:

When selecting a data source, you should ask:

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

Standardizing formats means changing entries like "CRICKET" to:

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

Data Validation is important for:

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

A good problem is one that can be answered by:

Redundancy handling is done in:

Data which has not been checked or cleaned:

tool help to validate data:

Analyzing data helps us make decisions based on:

Which method is used to find meaning from data?

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

To avoid bias, we should:

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

Using dropdowns or checkboxes in surveys helps to:

How many types of common Data Errors?

Which of the following allow user to focus on Project?

Total number of steps in DSLC:

IoT is useful in:

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

Problem understanding means:

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

Method in which we asked question and record answers:

How many type of Data validation techniques are there?

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

Find trends & patterns involved in:

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

Next step after Problem identification:

Final step of DSLC method:

Writing your objectives like a checklist helps to:

When we refine a problem, we:

Share the results is called:

Public data collection method is:

After data cleaning next step is:

DSLC stands for:

Importance to setting clear objective:

Which allow software to collect data from websites or applications?

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