Introduction to data science

3. Which of the following focuses on the discovery of (previously) unknown properties on the data?

Data mining
Big Data
Data wrangling
Machine Learning

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4. Which of the following is the most important language for Data Science?

Java
Ruby
R
None of the mentioned

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Data Science?" class="read-more button" href="https://exam.pscnotes.com/mcq/which-of-the-following-is-the-most-important-language-for-data-science/#more-59513">Detailed SolutionWhich of the following is the most important language for Data Science?

5. Which step in the Data Science process involves assessing the quality of collected data?

Data Collection
Data Cleaning
Data Validation
Data Visualization

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0 576 512"> Subscribe on YouTube quality of collected data?" class="read-more button" href="https://exam.pscnotes.com/mcq/which-step-in-the-data-science-process-involves-assessing-the-quality-of-collected-data/#more-59491">Detailed SolutionWhich step in the Data Science process involves assessing the quality of collected data?

6. Standard normal RVs are always labelled as Z.

TRUE
nan
nan
nan

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48.3-47.8 11.4-42.9 11.4-132.3 11.4-132.3s0-89.4-11.4-132.3zm-317.5 213.5V175.2l142.7 81.2-142.7 81.2z"/> Subscribe on YouTube
normal RVs are always labelled as Z.

7. What is the primary purpose of data visualization in Data Science?

To make data more complicated
To simplify complex data
To increase data complexity
To store data

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class="screen-reader-text">What is the primary purpose of data visualization in Data Science?

8. Which of the following command help us to give message description?

git command -m
git command -d
git command -message
none of the mentioned

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9. Point out the wrong statement.

You need GitHub to use Git
GitHub allows you to share repositories with others
GitHub allows you to access others repositories
All of the mentioned

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10. Which of the following is a common method for dealing with missing data in a dataset?

Dropping missing values
Imputing missing values
Creating new features
Normalizing the data

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of the following is a common method for dealing with missing data in a dataset?

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