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Here, you will find The Data Scientist’s Toolbox Exam Answers in Bold Color which are given below.
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About The Data Scientist’s Toolbox Course
This course will introduce you to the fundamental techniques and concepts used by data scientists. The course introduces students to the types of information, research questions, and analysis techniques used by data analysts and scientists.
Course Apply Link – The Data Scientist’s Toolbox
The Data Scientist’s Toolbox Quiz Answers
Week 01: Summative Quiz Answers
Q1. Which of these is NOT one of the main skills embodied by data scientists?
- Artificial intelligence
- Hacking skills
- Substantive expertise
Q2. What is the most important thing in Data Science?
- The question you are trying to answer
- Statistical inference
- Working with large data sets
Q3. Which of these might be a good title for a forum post?
- URGENT! R isnt working!
- Removing rows with NAs in data.frame using subset(), R 3.4.3
- How do I get rnorm() to work?
Q4. What is the first step in the data science process?
- Communicate your findings
- Exploring the data
- Generating the question
Q5. Which of these is an example of a quantitative variable?
- Educational level
Week 02: Summative Quiz Answers
Q1. What does base R focus on?
- Statistical analysis
- Artificial intelligence
Q2. What is RStudio?
- A graphical user interface for R
- Version control software
- A programming language
Q3. What is the name of the quadrant in the bottom left corner of RStudio, in the default layout?
Q4. What command lists your R version, operating system, and loaded packages?
Q5. What file extension do Projects in R use?
Week 03: Summative Quiz Answers
Q1. What is a good example of a message to accompany a commit?
- Modified linear model of height to include new covariate, genotype
- Fixed problem with linear model
- Updated thing
Q2. Question 2On each repository page in GitHub, in the top right-hand corner there are three options. They are:
- Watch, star, fork
- Pull, clone, fork
- Commit, contributors, issues
Q3. Which of the following will initiate a git repository locally?
- git init
- git remote add
- git boom
Q4. What is the order of commands to send a file to GitHub from within RStudio?
- Commit > Push
- Stage > Commit message > Commit > Push
- Pull > Push > Commit
Q5. How do you add all of the contents of a directory to version control?
- git add .
- cd ~/dir/name/of/path/to/file
- git commit -m Message
Week 04: Summative Quiz Answers
Q1. What is the format for including a link that appears as blue text in your markdown document?
- [text that is shown](link.com)
- (link.com)[text that is shown]
- (text that is shown)[link.com]
Q2. Which of the following describes a predictive analysis?
- Using data collected in the past to predict values in the future
- Finding if one variable is related to another one
- Showing the effect on a variable of changing the values of another variable
Q3. We collect data on all the songs in the Spotify catalog and want to
summarize how many are country-western, hip-hop, classic rock, or other.
What type of analysis is this?
Q4. What might a confounder be in an experiment looking at the relationship
between the prevalence of white hair in a population and wrinkles?
- Socioeconomic status
Q5. Which one of the following is an example of structured data?
- The text from a series of books
- Lung x-ray images
- A table of names and student grades
More About This Course
This course will introduce you to the fundamental techniques and concepts used by data scientists. The course introduces students to the types of information, research questions, and analysis techniques used by data analysts and scientists. This course is split into two parts. The first provides a high-level overview of the concepts underlying the transformation of raw data into useful insights. The second is a hands-on orientation to the software packages (such as version control, markdown, git, GitHub, R, and RStudio) that will be utilized during the course of the program.
This class is a component of several different sets of studies.
You can use this class for several different Specializations or Professional Certificates. The following courses will recognize this course’s completion as credit:
- Data Science Specialization
- Data Science: Foundations using R Specialization
Here’s What You’ll Discover
- Install and configure R, R Studio, Github, and other necessary software
- Learn about the information, challenges, and resources that data analysts rely on
- Defend crucial ideas in experimental design
- Build a repository on Github.
SKILLS YOU WILL Gain
- Research Based on Scientific Data
- Computing using R
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