Thẻ ghi nhớ: ADY201m FALL24 | Quizlet

Walmart addressed its analytical needs by approaching Kaggle to host a competition for analyzing its proprietary data.
A. True.
B. False.

A. True

What is the average base salary of a data scientist reported by the New York Times?
A.$100,000
B. $150,000
C. $112,000
D. $16 per hour
E. $85,000 + Bonus

C. $112,000

According to professor Haider, the three important qualities to possess in order to succeed as a data scientist are:
A. Proficient in Programming.
B. Curious.
C. Good at Math and Statistics.
D. Judgemental.
E. Good Story Teller (Argumentative).

B. Curious
D. Judgemental
E. Good Story Teller (Argumentative).

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

A. False

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.
A. True.
B. False.

B. False

According to the reading, the author defines data science as the art of uncovering the hidden secrets in data.
A. Data science is a physical science like physics or chemistry
B. Data science is the art of uncovering the hidden secrets in data.
C. Data science is a way of understanding things and understanding the world.
D. Data science is what data scientists do.
E, Data science is some data and more science.

D. Data science is what data scientists do.

What is admirable about Dr. Patil's definition of a data scientist is that it limits data science to activities involving machine learning.
A. True.
B. False.

B. False

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.
A. True.
B. False.

A. True

According to the reading, the author defines data science as the art of uncovering the hidden secrets in data.
A. False.
B. True.

A. False

According to the reading, what is admirable about Dr. Patil's definition of a data scientist?
A. His definition limits data science to activities involving machine learning.
B. His definition is about weaving strong narratives into analytics.
C. His definition is inclusive of individuals from various academic backgrounds and training.
D. His definition excludes statistics.

C. His definition is inclusive of individuals from various academic backgrounds and training.

What is an example of a data reduction algorithm?
A. Prior Variable Analysis.
B. Cojoint Analysis.
C. A/B Testing.
D. Principal Component Analysis.

D. Principal Component Analysis.

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

B. False

"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:
A. Prototyping.
B. Overfitting.
C. Reverse engineering.
D. In-sample forecast.

D. In-sample forecast.

Regression is a statistical technique developed by Blaise Pascal.

A. False.
B. True.

A. False.

The author discovered that houses located more than 2.5 kms to shopping centres sold for less than the rest.

A. True.
B. False.

B. False

"What are typical land taxes in a house sale?" is a question that can be put to regression analysis.

A. True.
B. False

B. False

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

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

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

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

True.
False.

False

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

A False.
B True.

True

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

False

The United States Economic Forecast is a publication by:

A. Cambridge University Press.
B. McGraw-Hill Education.
C. Deloitte University Press
D. McKinsey Publication Inc.

C. Deloitte University Press

According to the Module 1 reading, "The Sexiest Job in the 21st Century", a report published by the McKinsey Global Institute, in what year a shortage of 140,000 - 190,000 people with deep analytical skills in the United States is projected?

A. 2017
B. 2018
C. 2015
D. 2020

B. 2018

According to the Module 1 reading, "The Sexiest Job in the 21st Century", what magazine called Data Science the sexiest job of the 21st century?

A. Forbes
B. Harvard Business Review
C. Bloomberg Businessweek
D. Wired

B. Harvard Business Review

According to the Module 1 reading "What Makes Someone a Data Scientist", this chief economist at Google declared that "the sexy job in the next ten years will be statisticians". What is his name:

A. Larry Page
B. Hal Varian
C. Sal Barian
D. Sundar Pichai

B. Hal Varian

According to the Module 1 reading "What Makes Someone a Data Scientist", the author defines a _______ as someone who finds solutions to problems by analyzing data using appropriate tools and then tells stories to communicate their findings to the relevant stakeholders.

A. Data Engineer
B. Data analyst
C. Statistician
D. Data scientist

D. Data scientist

According to the Module 2 reading "Data Mining", the ______ of a data mining exercise largely depends on the quality of the data.

A. Results
B. Input
C. Difficulty
D. Output

D. Output

Based on the Module 2 reading, "Regression", the author's research on residential real estate properties quantified what?

A. The relationship between housing and transportation.
B. The magnitude of relationships between housing prices and different determinants.
C. The likelihood of a house selling rapidly.
D. That people hold no basic perceptions on real estate properties.

B. The magnitude of relationships between housing prices and different determinants.

Based on the Module 2 reading, "Regression", the author's research revealed that adding an additional washroom had a bigger impact than adding what type of room?

A. Playroom
B. Theater room
C. Bedroom
D. Dining room

C. Bedroom

According to the Module 3 reading, "The Final Deliverable", the ultimate purpose of _________ is to communicate findings to stakeholders to formulate policy or strategy.

A. Big data
B. Sales
C. Analytics
D. Data science

C. Analytics

Based on The Module 3 reading, "The Final Deliverable", it mentions a common role of a data scientist is to use what to build a narrative to communicate findings to stakeholders?

A. Strategies
B. Spreadsheets
C. Big data
D. Analytics insights

D. Analytics insights

Based on the Module 3 reading, "The Report Structure", regardless of the length of the ___________, the author recommends that it includes a cover page, table of contents, executive summary, a methodology section, and a discussion section.

A. Final deliverable
B. Presentation
C. Spreadsheet
D. Data set

A. Final deliverable

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

A. True.
B. False.

False

According to the Module 1 reading, "The Sexiest Job in the 21st Century", which of the following jobs was called by the Harvard Business Review the sexiest job of the 21st century?

A. Coal Mining.
B. Math and Statistics.
C. Data Science.
D. Renewable Energy Engineering.
E. Engineering.

C. Data Science.

According to the reading Module 1 "What Makes Someone a Data Scientist", the author defines a data scientist as someone who finds solutions to what, by analyzing data using appropriate tools and then tells stories to communicate their findings to the relevant stakeholders?

A. Drawbacks
B. Problems
C. Questions
D. Complications

B. Problems

According to the Module 2 reading "Data Mining", the output of what type of exercise largely depends on the quality of the data?

A. Data processing
B. Hypothetical
C. Data mining
D. Experimental

C. Data mining

According to the Module 2 reading, "Data Mining", when data is missing in a systematic way, you should determine the impact of _______ on the results and whether the missing data can be excluded from the analysis.

A. Changing data
B. Extrapolation
C. Averages
D. The missing data

D. The missing data

Based on the Module 2 reading, "Regression", the author's research on residential real estate properties quantified what?

A. That people hold no basic perceptions on real estate properties.
B. The likelihood of a house selling rapidly.
C. The relationship between housing and transportation.
D. The magnitude of relationships between housing prices and different determinants.

D. The magnitude of relationships between housing prices and different determinants.

The reading in Module 3, "The Final Deliverable", mentions a common role of a ____________ is to use analytics insights to build a narrative to communicate findings to stakeholders.

A. CEO
B. CFO
C. Data scientist
D. Engineer

C. Data scientist

Based on the Module 3 reading, "The Report Structure", regardless of the length of the ___________, the author recommends that it includes a cover page, table of contents, executive summary, a methodology section, and a discussion section.

A. Presentation
B. Spreadsheet
C. Final deliverable
D. Data set

C. Final deliverable

Based on the Module 3 reading, "The Report Structure", an introductory section is always helpful in setting up the problem for the reader who might be what?

A. New to the topic
B. Looking for the statistical calculations
C. Wanting to know the research methods
D. In sales

A. New to the topic

The first stage of the data science methodology is Data Understanding.

A. True
B. False

B. False

(The first stage of the data science methodology is Business Understanding.)

The main purpose of the analytic approach is identifying what type of patterns will be needed to address the posed question most effectively.

A. True
B. False

A. True

Which machine learning algorithm was implement in the case study discussed in the videos?

A. k-Nearest Neighbor.
B. Decision Tree Classification.
C. Logistic Regression.
D. Support Vector Machines.

B. Decision Tree Classification.

In the case study, during the Data Understanding stage, data scientists discovered that not all the congestive heart failure admissions that were expected were being captured. What action did they take to resolve the issue?

A. The data scientists looped back to the Business Understanding stage to redefine the requirements.
B. The data scientists looped back to the Data Collection stage, adding secondary and tertiary diagnoses, and building a more comprehensive definition of congestive heart failure admission.
C. The data scientists added the missing data manually.
D. The data scientists did not need to do anything. In this case, expectations for the data were incorrect.

B. The data scientists looped back to the Data Collection stage, adding secondary and tertiary diagnoses, and building a more comprehensive definition of congestive heart failure admission.

During the Data Preparation stage, clients and stakeholders aggregate the data and merge them from different sources, enabling data scientists to use clean data in the analysis.

A. True
B. False

B. False

Select the correct statement about the Data Preparation stage of the data science methodology.

A. Data Preparation is typically the least time-consuming methodological step.
B. Data Preparation involves dealing with missing improperly coded data and can include using text analysis to structure unstructured or semi-structured text data.
C. Data Preparation cannot be accelerated through automation.
D. None of the above statements are correct.

B. Data Preparation involves dealing with missing improperly coded data and can include using text analysis to structure unstructured or semi-structured text data.

The Modeling stage is followed by the Analytic Approach stage.

A. True
B. False

B. False

Select the correct statement(s) about the Model Evaluation stage of the data science methodology.

A. Model Evaluation includes ensuring that the data are properly handled and interpreted.
B. Model Evaluation includes ensuring the model is designed as intended.
C. Model Evaluation cannot include statistical significance testing.
D. Model Evaluation includes ensuring that the model is working as intended.

D. Model Evaluation includes ensuring that the model is working as intended.
A. Model Evaluation includes ensuring that the data are properly handled and interpreted.

A data scientist determines that building a recommender system is the solution for a particular business problem at hand. This is represented by the Modeling stage of the data science methodology?

A. True
B. False

B. False

A car company asked a data scientist to determine what type of customers are more likely to purchase their vehicles. However, the data comes from several sources and is in a relatively "raw format". What kind of processing can the data scientist perform on the data to prepare it for the Modeling stage?
A. Feature Engineering.
B. Transforming the data into more useful variables.
C. Combining the data from the various sources.
D. Addressing missing invalid values.

1. Only options A and D are correct.
2. Only option C is correct.
3. None of the options are correct.
4. All of the options are correct.

4. All of the options are correct.

Data scientists may use either a "top-down" approach or a "bottom-up" approach to data science. These two approaches refer to:

A. "Top-down" approach - models are fit before the data is explored. "Bottom-up" approach - data is explored, and then a model is fit.

B. "Top-down" approach - first defining a business problem then analyzing the data to find a solution. "Bottom-up" approach - starting with the data, and then coming up with a business problem based on the data.

C. "Top-down" approach - using massively parallel, warehouses with huge data volumes as the data source. "Bottom-up" approach - using a sample of small data before using large data.

D. "Top-down" approach - the data, when sorted, is modeled from the "top" of the data towards the "bottom". "Bottom-up" approach - the data is modeled from the "bottom" of the data to the "top".

B. "Top-down" approach - first defining a business problem then analyzing the data to find a solution. "Bottom-up" approach - starting with the data, and then coming up with a business problem based on the data.

Which of the following is the first state of the data science methodology?

A. Business Understanding
B. Data Collection
C. Data Understanding
D. Modeling

A. Business Understanding

______________________ is an important stage in the data science methodology because it clearly defines the problem and the needs from a business perspective.

A. Modeling
B. Data Collection
C. Business Understanding
D. Data Understanding

C. Business Understanding

Which of the following analogies is used in the videos to explain the Data Requirements and Data Collection stages of the data science methodology?

A. You can think of the Data Requirements and Data Collection stages as building an outpatient clinic for patients with congestive heart failure, where the medical condition is the data and the patients are the ingredients.

B. You can think of the Data Requirements and Data Collection stages as a cooking task, where the problem at hand is a recipe, and the data to answer the question is the ingredients.

B. You can think of the Data Requirements and Data Collection stages as a cooking task, where the problem at hand is a recipe, and the data to answer the question is the ingredients.

In the Data Collection stage, techniques such as ___________ and visualization can be applied to the data set, to assess the content, quality, and initial insights about the data.

A. Descriptive statistics
B. Data manipulation
C. The supervised method
D. The unsupervised method

A. Descriptive statistics

A type I error is a ____________.

A. False-positive error
B. Hypothesis error
C. False-alarm error
D. False-negative error

A. False-positive error

The Data Understanding stage encompasses ____________________.

A. Transforming data.
B. Removing redundant data.
C. Sorting the data.
D. All activities related to constructing the dataset.

D. All activities related to constructing the dataset.

The Data Preparation stage involves what?

A. Addressing missing values.
B. Correcting invalid values and addressing outliers.
C. Removing duplicate data.
D. Formatting the data.
E. All of the above

E. All of the above

The final stages of the data science methodology are an iterative cycle between which of the different stages?

A. Modelling, Evaluation, Data Understanding, Data Preparation, and Deployment.
B. Modelling, Evaluation, Deployment, and Feedback.
C. Modelling, Data Preparation, Deployment, and Feedback.
D. Data Understanding, Data Preparation, Evaluation, and Modelling.

B. Modelling, Evaluation, Deployment, and Feedback.

Deploying a model into production represents the beginning of an iterative process from ________, then Model Refinement, and to Redeployment.

A. Scalability
B. Data Storage
C. Feedback
D. None of the above

C. Feedback

As a data scientist what is typically NOT used for exploratory analysis of data?

A. Vector machines, Descriptive statistics
B. Deep Learning, Data visualization
C. Clustering, Deep learning
D. Clustering, Data visualization

D. Clustering, Data visualization

Select the correct statement.

A. The first stage of the data science methodology is Data Understanding.
B. The first stage of the data science methodology is Data Collection.
C. The first stage of the data science methodology is Modeling.
D. The first stage of the data science methodology is Business Understanding.

D. The first stage of the data science methodology is Business Understanding.

What is an important stage in the data science methodology because it clearly defines the problem and the needs from a business perspective?

A. Data Collection
B. Modeling
C. Business Understanding
D. Data Understanding

C. Business Understanding

In the Data Collection stage, techniques such as descriptive statistics and visualization can be applied to the data set, to assess the content, quality, and initial insights about the data

A. True
B. False

A. True

A training set is used for what?

A. Statistical analysis
B. Predictive modeling
C. Descriptive modeling
D. Data Visualization

B. Predictive modeling

A statistician calls a false-negative, a type I error, and a false-positive, a type II error.

A. True
B. False

B. False

In what stage would you properly format the data?

A. The Data Preparation stage
B. The Modeling stage
C. The Data Requirements stage
D. The Data Understanding stage

A. The Data Preparation stage

The final stages of the data science methodology are an iterative cycle between which of the different stages?

A. Modelling, Data Preparation, Deployment, and Feedback.
B. Modelling, Evaluation, Data Understanding, Data Preparation, and Deployment.
C. Modelling, Evaluation, Deployment, and Feedback.
D. Data Understanding, Data Preparation, Evaluation, and Modelling.

C. Modelling, Evaluation, Deployment, and Feedback.

Select the correct sentence about the data science methodology as explained in the course.

A. The data science methodology does not depend on a specific set of technologies or tools.
B. The data science methodology always starts with Business Understanding.
C. The data science methodology is an iterative process.
D. All of the above

D. All of the above

What do data scientists typically use for exploratory analysis of data and to get acquainted with it?

A. They begin with regression, classification, or clustering.
B. They use deep learning.
C. They use support vector machines and neural networks as feature extraction techniques.
D. They use descriptive statistics and data visualization techniques.

D. They use descriptive statistics and data visualization techniques.

Assume there exists an INSTRUCTOR table with several columns including FIRSTNAME, LASTNAME, etc. Which of the following is the most likely result set for the following query:

SELECT DISTINCT(FIRSTNAME) FROM INSTRUCTOR

What does the following SQL statement do?

UPDATE INSTRUCTOR SET LASTNAME = 'Brewster' WHERE LASTNAME = 'Smith'

The SELECT statement is called a query, and the output we get from executing the query is called a result set.
A. True
B. False

A. True

Which of the following SQL statements will delete the students with the last name Smith?

A. DELETE 'Smith' FROM STUDENTS
B. DELETE FROM TEACHERS WHERE LAST_NAME = 'Smith'
C. DELETE FROM STUDENTS WHERE LAST_NAME = 'Smith'
D. DELETE FROM STUDENTS WHERE LAST_NAME FROM 'Smith'

C. DELETE FROM STUDENTS WHERE LAST_NAME = 'Smith'

The primary key of __________ uniquely identifies each row in a table.

1. A customer
2. A relational table
3. A database
4. A name

2. A relational table

The basic categories of the SQL language based on functionality are ________ and Data Manipulation Language (DML).

A. Data Input Language (DIL)
B. Data Entry Language (DEL)
C. Data Definition Language (DDL)
D. Data Update Language (DUL)

C. Data Definition Language (DDL)

You want to retrieve a list of books that have between 450 and 600 pages. Which clause would you add to the following SQL statement: SELECT Title, Pages FROM Book ________________________________

A. WHERE Pages 450 - 600
B. IF Pages >= 450 and Pages <= 600
C. WHERE Pages = 450
D. WHERE Pages >= 450 and pages <= 600

D. WHERE Pages >= 450 and pages <= 600

Which of the following queries will retrieve the last name of the employee who earns the lowest salary?

A. SELECT LAST_NAME, MIN(SALARY) FROM EMPLOYEES GROUP BY F_NAME

B. SELECT FIRST_NAME FROM EMPLOYEES WHERE SALARY IS LOWEST

C. SELECT LAST_NAME FROM EMPLOYEES WHERE SALARY =
(SELECT MIN(SALARY) FROM EMPLOYEES)

D. SELECT MIN(SALARY) FROM EMPLOYEES

C. SELECT LAST_NAME FROM EMPLOYEES WHERE SALARY =
(SELECT MIN(SALARY) FROM EMPLOYEES)

A ____________ is a control structure that enables traversal over the records in a database.

A. Import
B. Database cursor
C. Connection
D. Primary key

B. Database cursor

Which of the following SQL statements will delete the authors with IDs of A10 and A11?

A. DELETE FROM AUTHOR WHERE AUTHOR_ID IS ('A10', 'A11')
B. D: DELETE AUTHOR_ID IS ('A10', 'A11') FROM AUTHOR
C. DELETE ('A10', 'A11') FROM AUTHOR
D. DELETE FROM AUTHOR WHERE AUTHOR_ID IN ('A10', 'A11')

D. DELETE FROM AUTHOR WHERE AUTHOR_ID IN ('A10', 'A11')

What does the primary key of a relational table do?

A. The primary key uniquely identifies each column in a table.
B. The primary key uniquely identifies each attribute in a table.
C. The primary key uniquely identifies each row in a table.
D. The primary key uniquely identifies each relation in a table.

C. The primary key uniquely identifies each row in a table.

When querying a table called Representative that contains a list of representatives and the state that they represent, which of the following queries will return the number of representatives from each state?

A. SELECT State, distinct(State) FROM Representative GROUP BY State
B. SELECT State, count(State) FROM Representative
C. SELECT distinct(State) FROM Representative
D. SELECT State, count(State) FROM Representative GROUP BY State

D. SELECT State, count(State) FROM Representative GROUP BY State

A database cursor is a control structure that enables traversal over the records in a database. (T/F)

False
True

True

SQL is what type of database management system?

A. Object-oriented
B. Network
C. Hierarchical
D. Relational

D. Relational

PyTorch is what type of Python library?

A. HTTP
B. Machine learning
C. Linear algebra
D. Data visualization

B. Machine learning

Generally speaking, which type of model is used to predict a numerical value, such as the potential sales price of a used car?

A. Clustering model
B. Regression model
C. Classification model

B. Regression model

Data governance can also be called?

A. Data stewardship
B. Perimeter security
C. Data asset management
D. Data strategy

C. Data asset management

What is a great alternative to Jupyter Notebooks when programming in R?

A. VSCode
B. Notepad
C. D: Spyder
D. RStudio

D. RStudio

How is the R programming language different than Python?

A. It is a general purpose language
B. It's primary objective is deployment and production
C. It was built by statisticians and their specific language

C. It was built by statisticians and their specific language

Which of the following functions does RStudio provide?

A. Editing and execution of R code.
B. Documenting R code applications.
C. Creating relationships between data tables.
D. Storing data in tables.

A. Editing and execution of R code.

Which of the following statements about Jupyter Notebook is correct?

A. Jupyter Notebook provides storage of massive quantities of data in data lakes.
B. Jupyter Notebook is a commercial product of IBM.
C. Jupyter Notebook is only available if installed locally on your computer.
D. Jupyter Notebook supports the Visualization of data in charts.

D. Jupyter Notebook supports the Visualization of data in charts.

What capability monitors and manages models to operate trusted AI?

A. AutoAI
B. Watson Knowledge Catalog
C. OpenScale
D. Modeler Flows

C. OpenScale

How does Data Refinery help build repeatable Data Pipelines for workloads of almost any size?

A. Only a fixed workload size is supported.
B. Manually write APIs to provide automation.
C. Feature is available only in the UI, not API.
D. Not supported.
E. Create a scheduled Job and use a custom environment to run the data flow/pipeline on different workloads.

E. Create a scheduled Job and use a custom environment to run the data flow/pipeline on different workloads.

What type of node is used to define metadata for features in Modeler flows?

A. A data source node
B. A type node
C. All of the above
D. A modeling node
E, An output node

B. A type node

What does SPSS stand for?

A. Static Package for the Social Sciences
B. Statistical Package for the Social Society
C. Statistical Package for the Social Sciences
D. Statistical Packing for the Social Sciences

C. Statistical Package for the Social Sciences

Which Data Science category enables you to present data in the form of charts, plots, and maps?

A. Data Visualization
B. Data Integration and Transformation
C. Model Building
D. Data Management

A. Data Visualization

Which Data Science category uses tools like Fiddler to track the performance of deployed models in a production environment?

A. Data Management
B. Data Integration and Transformation
C. Data Visualization
D. Model Monitoring

D. Model Monitoring

Which open-source tool is used for model deployment?

A. ModelDB
B. MySQL
C. Apache PredictionIO
D. Git

C. Apache PredictionIO

Which open-source tool is used to version data and annotate the data with metadata?

A. Apache Atlas
B. Kubernetes
C. Apache AirFlow
D. Hue

A. Apache Atlas

Which feature differentiates Apache Zeppelin from Jupyter Notebooks?

A. Ability to unify programming, execution, and debugging into one tool
B. Ability to open different types of files
C. Plotting capability
D. Ability to unify documentation and code in a single documen

A. Ability to unify programming, execution, and debugging into one tool