What is Data Science? Coursera Quiz Answers

About What is Data Science? Course

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year.

Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.

This course is part of multiple programs:

This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

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What is Data Science? Quiz Answers

Week 1 – Quiz 1: Data Science: The Sexiest Job in the 21st Century

Q1. Which of the following jobs was called by the Harvard Business Review the sexiest job of the 21st century?

  • Coal Mining
  • Data Science
  • Math and Statistics
  • Renewable Energy Engineering

Q2. According to the report by the McKinsey Global Institute, by 2018, it is projected that there will be a shortage of 140,000 – 190,000 people with deep analytical skills in the world.

  • True
  • False

Q3. Walmart addressed its analytical needs by approaching Keggle to host a competition for analyzing its proprietary data.

  • True
  • False

Q4. The New York Times reported that the average base salary of a data scientist is $85,000 + a competitive bonus.

  • True
  • False

Q5. According to professor Haider, the three important qualities to possess in order to succeed as a data scientist are curious, judgemental, and proficient in programming.

  • True
  • False

Extra Questions

Q6. Harvard Business Review called data science the sexiest job in the 21st century.

  • True
  • False

Q7. How is Walmart reported to have addressed its analytical needs?

  • Social media
  • Code sharing
  • Crowdsourcing
  • Outsourcing
  • None of the options is correct

Q8. What is the average base salary of a data scientist reported by the New York Times?

  •  $100,000
  •  $150,000
  •  $112,000
  •  $16 per hour
  •  $85,000 + Bonus

Q9. According to professor Haider, the three important qualities to possess in order to succeed as a data scientist are:

  • Curious.
  • Judgemental.
  • Proficient in Programming.
  • Good at Math and Statistics.
  • Good Story Teller (Argumentative).

Quiz 2: What Makes Someone a Data Scientist?

Q1. Hal Varian, the chief economist at Google, declared that “the sexy job in the next ten years will be

  • Physicists
  • Statisticians
  • Engineers
  • Computer Scientists                

Q2. The author defines a data scientist as someone who finds solutions to problems by analyzing data using appropriate tools and then tells stories to communicate their finding to the relevant stakeholders.

  • True
  • False

Q3. According to the reading, the author defines data science as the art of uncovering hidden secrets in data.

  • True
  • False

Q4. What is admirable about Dr. Patil’s definition of a data scientist is that it limits data science to activities involving machine learning.

  • True
  • False

Q5. According to the reading, the characteristics exhibited by the best data scientists are those who are curious, ask good questions, and are O.K. dealing with unstructured situations.

  • True
  • False

Extra Questions

Q1. Hal Varian, the chief economist at Google, declared that “the sexy job in the next ten years will be computer scientists”.

  • True
  • False

Q2. According to the reading, how does the author define data science?

  • Data science is what data scientists do.
  • Data science is some data and more science.
  • Data science is a physical science like physics or chemistry
  • Data science is the art of uncovering the hidden secrets in data.
  • Data science is a way of understanding things and understanding the world.

Q3. According to the reading, what is admirable about Dr. Patil’s definition of a data scientist?

  • His definition excludes statistics.
  • His definition limits data science to activities involving machine learning
  • His definition is about weaving strong narratives into analytics.
  • His definition is inclusive of individuals from various academic backgrounds and training.

Q4. According to the reading, the characteristics exhibited by the best data scientists are those who are curious, ask good questions, and have at least 10 years of experience.

  • True
  • False

Q5. According to the reading, what characteristics are said to be exhibited by the best data scientists?

  • Thinkers who are really curious and hold a Ph.D.
  • Really curious people who ask good questions.
  • Curious individuals who ask good questions and are O.K. dealing with unstructured situations
  • Really curious engineers and statisticians.
  • Really curious people who ask good questions and have at least 10 years of experience.

Week 2 – Quiz 3: Data Mining

Q1. According to the reading, the output of a data-mining exercise largely depends on:

  • The data scientist
  • The quality of the data
  • The scope of the project
  • The programming language used

Q2. Prior Variable Analysis and Principal Component Analysis are both examples of a data reduction algorithm.

  • True
  • False

Q3. After the data are appropriately processed, transformed, and stored, what is a good starting point for data mining?

  • Machine learning.
  • Data Visualization.
  • Non-parametric methods.
  • Creating a relational database.

Q4. When data are missing in a systematic way, you can simply extrapolate the data or impute the missing data by filling in the average of the values around the missing data.

  • True
  • False

Q5. “Formal evaluation could include testing the predictive capabilities of the models on observed data to see how effective and efficient the algorithms have been in reproducing data.” This is known as:

  • Prototyping.
  • Overfitting.
  • In-sample forecast.
  • Reverse engineering. 

Q6. What is an example of a data reduction algorithm?

  • Cojoint Analysis.
  • A/B Testing.
  • Prior Variable Analysis.
  • Principal Component Analysis.  

Q7. After the data are appropriately processed, transformed, and stored, machine learning and non-parametric methods are a good starting point for data mining.

  • True 
  • False

Q8. In–sample forecast is the process of formally evaluating the predictive capabilities of the models developed using observed data to see how effective the algorithms are in reproducing data.

  • True
  • False

Quiz 4: Regression

Q1. The author discovered that all else being equal, houses located less than 5kms but more than 2.5 km to shopping centers sold for more than the rest.

  • True
  • False

Q2. The author discovered that houses located more than 2.5 km to shopping centers
sold for less than the rest.

  • True
  • False

Q3. Based on the reading, which of the following are questions that can be put to
regression analysis?

  • Do homes with brick exterior sell for less than homes with stone exterior?
  • Do homes with brick exterior sell in rural areas?
  • What is the impact of lot size on housing price?
  • What are typical land taxes in a house sale?

Q4. The real added value of the author’s research on residential real estate properties
is quantifying people’s preferences of different transport services.

  • False
  • True

Q5. Regression is a statistical technique developed by Sir Frances Galton.

  • False
  • True

Q6. According to the reading, the author discovered that an additional bedroom adds
more to the housing prices than an additional washroom.

  • False
  • True

Q7. What did the Author’s Research reveal about proximity to large shopping centres?

  • The author discovered that houses located more than 2.5 kms to shopping centres sold for less than the rest.
  • The author discovered that proximity to large shopping centres didn’t have any significant impact on the prices of housing units.
  • The author discovered that proximity to large shopping centres had a nonlinear impact on the housing prices.
  • The author discovered that houses located more than 5 kms to shopping centres sold for less than the rest.

Q8. ”How much does a finished basement contribute to the price of a housing unit?” is a question that can be put to regression analysis.

  • False
  • True

Week 3 – Quiz 5 The Final Deliverable

Q1. The report discussed in the reading successfully did the job of using data and analytics to generate the likely economic scenarios.

  • True
  • False

Q2. The ultimate purpose of analytics is to communicate findings to stakeholders to formulate policy or strategy.

  • True
  • False

Q3. The Untied States Economic Forecast is a publication by McKinsey University Press.

  • True
  • False

Q4. The report discussed in the reading successfully did the job of:

  • Calculating projections for the economy
  • Summarizing pages and pages of research
  • Convincing the leadership team to act on an initiative
  • Using data and analytics to generate the likely economic scenarios

Q5. According to the reading, it is recommended that a team waits until the results of analytics are out before they can decide on the final deliverable.

  • True
  • False

Extra Questions

Q6. According to the reading, what is the ultimate purpose of analytics?

  • To evangelize data science
  • To facilitate meetings between sales and marketing
  • To efficiently store big data with minimum storage requirements
  • To communicate findings to stakeholders to formulate policy or strategy

Q7. What role of a data scientist is discussed in the reading?

  • Using insights to build a narrative to communicate findings
  • Managing a team of analysts to create a predictive model
  • Developing a strategy to fix the problems in the findings
  • Using the data to put together a story that the CEO wants to tell

Q8. According to the reading, in order to produce a compelling narrative, initial planning and conceptualizing of the final deliverable is of extreme importance.

  • True
  • False

Quiz 6: The Report Structure

Q1. Regardless of the length of the final deliverable, which of the following does the author recommend that you include:

  • Code
  • Discussion Section
  • Appendices
  • A Cover Page
  • Table of Contents

Q2. An introductory section is always helpful in introducing the research methods and presenting the statistical calculations.

  • True
  • False

Q3. The results section is where you present:

  • The empirical findings.
  • OR Squared.
  • The methods used.
  • The conclusion.

Q4. The discussion section is where you introduce the research methods and data sources used for the analysis.

  • True
  • False

Q5. Adding a list of references and an acknowledgment section are examples of housekeeping, according to the author.

  • True
  • False

Extra Questions

Q6. The results section is where you craft your main arguments and present your conclusion.

  • True
  • False

Q7. The discussion section is where you:

  • Highlight how your findings provide the ultimate missing piece to the puzzle
  • Introduce the research methods and data sources used for the analysis
  • Refer the reader to the research question and the knowledge gaps you identified earlier
  • Rely on the power of narrative to enable numbers to communicate your important findings to the readers

Q8. Regardless of the length of the final deliverable, the author recommends that it includes a cover page, table of contents, executive summary, methodology section, and a discussion section.

  • True
  • False

Q9. An introductory section is always helpful in:

  • Presenting the statistical calculations
  • Introducing the research methods
  • Setting up the problem for the reader who might be new to the topic
  • Advertising the product

Q10. The results section is where you craft your main arguments and present your conclusion

  • True
  • False

Q11. The discussion section is where you:

  • Introduce the research methods and data sources used for the analysis.
  • Highlight how your findings provide the ultimate missing piece to the puzzle.
  • Refer the reader to the research question and the knowledge gaps you identified earlier.
  • Rely on the power of narrative to enable numbers to communicate your important findings to the readers.

Final Exam Quiz Answer

Q1. Based on the videos and the reading material, how would you define a data scientist and data science? 

Data Science:

  • Data science is something that data scientist do.
  • Data science is a way of extracting insights from large volumes of disparate data.
  • Data science involves drawing patterns from seemingly random structured and unstructured type of data.

Data scientists:

  • Data scientists are curious and analytical thinkers who use a variety of math skills not limited to Mathematics, Statistics and Probability to solve a problem.
  • They apply different available methods and algorithms to draw insights and conclusions from various kinds of data.
  • After applying data science methodologies, they are effective communicators and story tellers who can present their findings often to present new findings or confirm what was initially suspected.

Q2. As discussed in the videos and the reading material, data science can be applied to problems across different industries. What industry are you passionate about and would like to pursue a data science career in? 

  • I am passionate about pursuing a data science career in the field of Healthcare with the main focus is improving the quality of care provided and making healthcare affordable. I would like to create models to predict diseases very early on by looking at various parameters of a person not limited to genetics, family history, lifestyle, and diet.

Q3. Based on the videos and the reading material, what are the ten main components of a report that would be delivered at the end of a data science project?

The 10 main components of a data science project report would be:

  • Cover Page with Author’s name, contacts, affiliations if any and publication date
  • Table of Contents containing main headings, list of contents and figures
  • Abstract / Executive summary to explain gist of the report
  • Introduction to explain the topic to new readers
  • Literature Review including citations of authors and data sources
  • Methodology section to explain the research methods and data sources used for analysis
  • Detailed Explanations including Results and discussion sections
  • Conclusions which generalize findings and identify possible future outcomes.
  • References
  • Acknowledgement and Appendices (if Needed)

Next Quiz Answers >>

Course 2: Tools for Data Science

All Quiz Answers of multiple Specializations or Professional Certificates programs:

Course 1: What is Data Science?

Course 2: Tools for Data Science

Course 3: Data Science Methodology

Course 4: Python for Data Science, AI & Development

Course 5: Python Project for Data Science

Course 6: Databases and SQL for Data Science with Python

Course 7: Data Analysis with Python

Course 8: Data Visualization with Python

Course 9: Machine Learning with Python

Course 10: Applied Data Science Capstone

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