Prepare Data for Exploration Coursera Quiz Answers – Networking Funda

Prepare Data for Exploration Coursera Quiz Answers

Prepare Data for Exploration Week 01 Quiz Answers

L2 Differentiate between data structures:

Q1. Fill in the blank: The running time of a movie is an example of _____ data.

  • continuous
  • discrete
  • internal
  • animated

Q2. What are the characteristics of unstructured data? Select all that apply.

  • May have an internal structure
  • Is not organized
  • Fits neatly into rows and columns
  • Has a clearly identifiable structure

Q3. Structured data enables data to be grouped together to form relations. This makes it easier for analysts to do what with the data? Select all that apply.

  • Store
  • Find
  • Analyze
  • Search

Q4. Which of the following is an example of unstructured data?

  • Contact saved on a phone
  • Rating of a local favorite restaurant
  • Email message
  • GPS location

Practice Quiz-2 Answers

L3 Generating data:

Q1. Which method of data collection is most often used by scientists?

  • Questionnaires
  • Interviews
  • Surveys
  • Observations

Q2. Fill in the blank: Organizations such as the U.S. Centers for Disease Control (CDC) often use data collected from other organizations. Data gathered by hospitals, then collected by the CDC is an example of _____.

  • multiple-party data
  • second-party data
  • third-party data
  • first-party data

Q3. A data analyst is working for a company that’s about to launch a new product. The analyst needs to collect qualitative data from customers during the product launch. What is the quickest, most accurate, and most relevant method of data collection in this scenario?

  • First-party data collection using an online survey
  • Second-party data results for a similar product
  • Third-party observations of customers shopping in stores
  • First-party customer interviews in focus groups

Practice Quiz-3 Answers

L4 Explore data types, fields, and values:

Q1. You’re working as a data analyst and you use a formula to average data in a spreadsheet. You receive an error based on the data type. Which data types in cells may have caused the error? Select all that apply.

  • Number
  • String
  • Duplicates
  • Text

Q2. The Boolean operator Not performs which of the following actions?

  • Changes the value of “true” to “false” or “false” to “true”
  • Changes the value of “true” to “null”
  • Ignores any value that is “false”
  • Converts the boolean values of “true” or “false” to their binary equivalents of “1” or “0”

Q3. Fill in the blank: Internet search engines are an everyday example of how Boolean operators are used. The Boolean operator _____ expands the number of results when used in a keyword search.

  • And
  • Not
  • Or
  • With

Q4. Which of the following statements accurately describes a key difference between wide and long data?

  • Every wide data subject has a single column that holds the values of subject attributes. Every long data subject has multiple columns.
  • Wide data subjects can have data in multiple columns. Long data subjects can have multiple rows that hold the values of subject attributes.
  • Wide data subjects can have multiple rows that hold the values of subject attributes. Long data subjects can have data in multiple columns.
  • Every wide data subject has multiple columns. Every long data subject has data in a single column.

Q5. Data transformation enables you to do what with your data?

  • Change the structure of the data
  • Retrieve the data faster
  • Inspect the data for accuracy
  • Restore the data after it has been lost

Prepare Data for Exploration Weekly Challenge 1 Answers

Q1. If you have a short time frame for data collection and need an answer immediately, you would have to use historical data.

  • True
  • False

Q2. Which of the following is an example of continuous data?

  • Box office returns
  • Movie run time
  • Movie budget
  • Leading actors in movie

Q3. Which of the following questions collects nominal qualitative data?

  • Is this your first time dining at this restaurant?
  • How many people do you usually dine with?
  • On a scale of 1-10, how would you rate your service today?
  • How many times have you dined at this restaurant?

Q4. Which of the following is a benefit of internal data?

  • Internal data is less vulnerable to biased collection.
  • Internal data is more relevant to the problem.
  • Internal data is more reliable and easier to collect.
  • Internal data is less likely to need cleaning.

Q5. A social media post is an example of structured data.

  • True
  • False

Q6. Fill in the blank: A Boolean data type can have _____ possible values.

  • two
  • three
  • infinite
  • 10

Q7. In long data, separate columns contain the values and the context for the values, respectively. What does each column contain in wide data?

  • A specific constraint
  • A unique format
  • A specific data type
  • A unique data variable

Q8. A data analyst is working in a spreadsheet application. They use Save As to change the file type from .XLS to .CSV. This is an example of a data transformation.

  • True
  • False

Prepare Data for Exploration Week 02 Quiz Answers

Practice Quiz-1 Answers

L2 Unbiased and objective data:

Q1. Which of the following are examples of sampling bias? Select all that apply.

  • A survey of high school students does not include homeschooled students.
  • A national election poll only interviews people with college degrees.
  • An online marketing analytics firm stores data in a spreadsheet.
  • A clinical study includes three times more men than women.

Q2. Two doctors look at the exact same image of a brain scan. The image is inconclusive, yet one doctor sees evidence of an abnormality in the brain. The other doctor sees a healthy brain. This is an example of sampling bias.

  • True
  • False

Practice Quiz-2 Answers

L3 Explore data credibility:

Q1. Which of the following are usually good data sources? Select all that apply.

  • Social media sites
  • Governmental agency data
  • Vetted public datasets
  • Academic papers

Q2. To determine if a data source is cited, you should ask which of the following questions? Select all that apply.

  • Who created this dataset?
  • Has this dataset been properly cleaned?
  • Is this dataset from a credible organization?
  • Is the data relevant to the problem I’m trying to solve?

Q3. Which of the following are qualities of a bad data source? Select all that apply.

  • The data source is out of date and irrelevant
  • The data source solely relies on third-party information
  • The data source is not cited or vetted
  • The data source is not missing any important information

Q4. A data analyst is analyzing sales data for the newest version of a product. They use third-party data about an older version of the product. For what reasons is this inappropriate for their analysis? Select all that apply.

The data is not accurate The data is biased

  • The data is not original
  • The data is not current

Practice Quiz-3 Answers

L4 Understand data ethics and privacy:

Q1. A data analyst uses fixed-length codes to represent data columns in order to remove personally identifying information from a dataset. What process does this scenario describe?

  • Data collection
  • Data sorting
  • Data visualization
  • Data anonymization

Q2. Data analysts never anonymize license plate numbers because that type of data can be easily seen whenever someone is out driving their car.

  • True
  • False

Q3. Before completing a survey, an individual reads information about how and why the data they provide will be used. What is this concept called?

  • Currency
  • Openness
  • Privacy
  • Consent

Practice Quiz-4 Answers

L5 Explaining open data:

Q1. What aspect of data ethics promotes the free access, usage, and sharing of data?

  • Consent
  • Transaction transparency
  • Privacy
  • Openness

Q2. What are the main benefits of open data?

  • Open data restricts data access to certain groups of people.
  • Open data increases the amount of data available for purchase.
  • Open data makes good data more widely available.
  • Open data combines data from different fields of knowledge.

Q3. Universal participation is a standard of open data. What are the key aspects of universal participation? Select all that apply.

  • Certain groups of people must share their private data.
  • Everyone must be able to use, re-use, and redistribute open data.
  • No one can place restrictions on data to discriminate against a person or group.
  • All corporations are allowed to sell open data.

Prepare Data for Exploration Weekly Challenge 2 Answers

Q1. Fill in the blank: A preference in favor of or against a person, group of people, or thing is called _____. It is an error in data analytics that can systematically skew results in a certain direction.

  • data interoperability
  • data collection
  • data anonymization
  • data bias

Q2. A university surveys its student-athletes about their experience in college sports. The survey only includes student-athletes with scholarships. What type of bias is this an example of?

  • Interpretation bias
  • Confirmation bias
  • Sampling bias
  • Observer bias

Q3. Which of the following are qualities of unreliable data? Select all that apply.

  • Biased
  • Vetted
  • Inaccurate
  • Incomplete

Q4. In data ethics, consent gives an individual the right to know the answers to which of the following questions? Select all that apply.

  • How will my data be used?
  • Why am I being forced to share my data?
  • Why is my data being collected?
  • How long will my data be stored?

Q5. An individual who provides their data has the right to know and understand all of the data-processing activities and algorithms used on that data. This concept refers to which aspect of data ethics?

  • Transaction transparency
  • Ownership
  • Consent
  • Currency

Q6. What is data privacy?

  • Providing free access, usage, and sharing of data
  • Applying well-founded standards of right and wrong that dictate how data is collected, shared, and used
  • Searching for or interpreting supporting information
  • Preserving a data subject’s information and activity for all data transactions

Q7. Data anonymization applies to both text and images.

  • True
  • False

Q8. The government of a large city collects data on the quality of the city’s infrastructure. Any business, nonprofit organization, or citizen can access the government’s databases and re-use or redistribute the data. Is this an example of open data?

  • Yes
  • No

Prepare Data for Exploration Week 03 Quiz Answers

Practice Quiz-1 Answers

Accessing different data sources:

Q1. A .CSV file saves data in a table format. What does .CSV stand for?

  • Compatible scientific variables
  • Comma-separated values
  • Calculated spreadsheet values
  • Cell-structured variables

Q2. A data analyst wants to bring data from a .CSV file into a spreadsheet. This is an example of what process?

  • Editing data
  • Filing data
  • Titling data
  • Importing data

Q3. A .CSV file makes it easier for data analysts to complete which tasks? Select all that apply.

  • Distinguish values from one another
  • Manage multiple tabs within a worksheet
  • Examine a small subset of a large dataset
  • Import data to a new spreadsheet

Practice Quiz-2 Answers

L2 Working with databases:

Q1. Fill in the blank: Normalized databases help avoid _____ data.

  • messy
  • abnormal
  • inaccurate
  • redundant

Q2. What does a database’s metadata tells a data analyst about its contents? Select all that apply.

  • Where the data came from
  • When the data was created
  • What the data is all about
  • Which type of analysis to perform on the data

Q3. What is the difference between a primary key and a foreign key?

  • A primary key is an identifier that references a column in which each value is identical. A foreign key references a column in which each value is unique.
  • A primary key is any column of data from a database. A foreign key is any column of data from a secondary database.
  • A primary key is an identifier that references a column in which each value is unique. A foreign key is a field within a table that’s a primary key in the original table.
  • A primary key is an identifier that references a column of relevant data within a database. A foreign key is an identifier that references a column of irrelevant data.

Q4. A data analyst at a PR firm needs to construct a database of celebrity clients. If their boss needs the data to be accessed as quickly as possible, the analyst should use a snowflake schema.

  • True
  • False

Q5. Fill in the blank: A relational database contains a series of _____ that can be connected to form relationships.

  • tables
  • cells
  • fields
  • schemas

Practice Quiz-3 Answers

L3 Managing data with metadata:

Q1. A large company has several data collections across its many departments. What kind of metadata indicates exactly how many collections the data lives in?

  • Descriptive metadata
  • Representative metadata
  • Administrative metadata
  • Structural metadata

Q2. Fill in the blank: Data _____ ensures that a company’s data assets are properly managed.

  • governance
  • quality control
  • maintenance
  • organization

Q3. A large metropolitan high school gives each of its students an ID number to differentiate them in its database. What kind of metadata are the ID numbers?

  • Representative
  • Administrative
  • Structural
  • Descriptive

Q4. A company needs to merge third-party data with its own data. The company can accomplish this with which of the following actions? Select all that apply.

  • Use metadata to standardize the data.
  • Use metadata to evaluate the third-party data’s quality and credibility.
  • Replace the incoming data’s metadata with its own company metadata.
  • Alter the company’s metadata to more closely reflect the incoming metadata.

Q5. The date and time a database was created is an example of which kind of metadata?

  • Unstructured
  • Descriptive
  • Administrative
  • Structural

Practice Quiz-4 Answers

L5 Sorting and filtering:

Q1. What is the process for arranging data into a meaningful order to make it easier to understand, analyze, and visualize?

  • Filtering
  • Reframing
  • Sorting
  • Prioritizing

Q2. Filtering by a particular criteria is an effective way to narrow the scope of a query. However, filtering is time-intensive because it can only be done one variable at a time.

  • True
  • False

Q3. A data analyst is reviewing a national database of real estate sales. They are only interested in sales of condominiums. How can the analyst narrow their scope?

  • Filter out condominium sales
  • Sort by condominium sales
  • Filter out non-condominium sales
  • Sort by non-condominium sales

Q4. A data analyst works for a rental car company. They have a spreadsheet that lists car ID numbers and the dates cars were returned. How can they sort the spreadsheet to find the most recently returned cars?

  • By return date, in ascending order
  • By return date, in descending order
  • By car numerical ID, in ascending order
  • By car numerical ID, in descending order

Q5. Fill in the blank: To keep a header row at the top of a spreadsheet, highlight the row and select _____ from the View menu.

  • Set
  • Freeze
  • Pin
  • Lock

Practice Quiz-5 Answers

L6 Working with large datasets in SQL:

Q1. In MySQL, what is a proper way to write a SELECT clause starter?

  • ‘SELECT’
  • “SELECT”
  • select
  • SELECT

Q2. Which case should be used when writing the column names in a database table?

  • Camel case
  • Sentence case
  • Lowercase
  • Snake case

Prepare Data for Exploration Weekly Challenge 3 Answers

Q1. Primary and foreign keys are two connected identifiers within separate tables. These tables exist in what kind of database?

  • Primary
  • Relational
  • Normalized
  • Metadata

Q2. Metadata is data about data. What kinds of information can metadata offer about a particular dataset? Select all that apply.

  • How to combine the data with another dataset
  • Which analyses to perform on the data
  • If the data is clean and reliable
  • What kinds of data it contains

Q3. Think about data as a student at a high school. In this metaphor, which of the following are examples of metadata? Select all that apply.

  • Classes the student is enrolled in
  • Student’s ID number
  • Grades the student earns
  • Student’s enrollment date

Q4. Think about data as a refrigerator. Which kind of metadata is the refrigerator’s product number?

  • Redundant
  • Administrative
  • Structural
  • Descriptive

Q5. What is the process that data analysts use to ensure the formal management of their company’s data assets?

  • Data integrity
  • Data governance
  • Data mapping
  • Data aggregation

Q6. Describe the key differences between a star and a snowflake schema. Select all that apply.

  • A star schema enables very fast data processing.
  • A snowflake schema enables very fast data processing. This should not be selected
  • A snowflake schema has one or more fact tables referencing any number of dimension tables. A star schema is an extension of a snowflake schema, with more dimensions and subdimensions.
  • A star schema has one or more fact tables referencing any number of dimension tables. A snowflake schema is an extension of a star schema, with more dimensions and subdimensions.

Q7. What are some key benefits of using external data? Select all that apply.

  • External data is always reliable.
  • External data is free to use.
  • External data has broad reach.
  • External data provides industry-level perspectives.

Q8. A data analyst reviews a database of Wisconsin car sales to find the last five car models sold in Milwaukee in 2019. How can they sort and filter the data to return the last five cars at the top? Select all that apply.

  • Filter out sales outside of Milwaukee
  • Filter out sales not in 2019
  • Sort by date in ascending order
  • Sort by date in descending order

Prepare Data for Exploration Week 04 Quiz Answers

Practice Quiz-1 Answers

L2 Effectively organize data:

Q1. Data analysts use guidelines to describe a file’s version, content, and date created. What are these guidelines called?

  • Naming references
  • Naming verifications
  • Naming attributes
  • Naming conventions

Q2. Data analysts use foldering to achieve what goals? Select all that apply.

  • To transfer files from one place to another
  • To organize folders into subfolders
  • To assign metadata about the folders
  • To keep project-related files together

Q3. Fill in the blank: To separate current from past work and reduce clutter, data analysts create _____. This involves moving files from completed projects to a separate location.

  • structures
  • archives
  • copies
  • backups

Q4. What is the process of structuring folders broadly at the top, then breaking down those folders into more specific topics?

  • Developing metadata
  • Creating a hierarchy
  • Assigning naming conventions
  • Producing a backup

Q5. Successful file naming conventions include information that’s useful when trying to locate or update a file. Which of the following are effective file names? Select all that apply.

  • AirportCampaign_53019_V01
  • May2019_AirportCampaignData_V03
  • Data_519
  • May30-2019_AirportAdvertisingCampaignResults_Terminals3-5_InclCustSurveyResponses_PLUS_IdeasforJune

Practice Quiz-2 Answers

L3 Securing data:

Q1. Fill in the blank: Data security involves using _____ to protect data from unauthorized access or corruption.

  • metadata
  • data validation
  • foldering
  • safety measures

Q2. When using data security measures, analysts can choose between protecting an entire spreadsheet or protecting certain cells within the spreadsheet.

  • True
  • False

Q3. What tools can data analysts use to control who can access or edit a spreadsheet? Select all that apply.

  • Filters
  • Sharing permissions
  • Tabs
  • Encryption

Prepare Data for Exploration Weekly Challenge 4 Answers

Q1. Fill in the blank: Naming conventions are _____ that describe a file’s content, creation date, or version.

  • frequent suggestions
  • common verifications
  • general attributes
  • consistent guidelines

Q2. A data analytics team uses data about data to indicate consistent naming conventions for a project. What type of data is involved in this scenario?

  • Metadata
  • Long data
  • Aggregated data
  • Big data

Q3. A data analyst creates a file that lists people who donated to their organization’s fund drive. An effective name for the file is: FundDriveDonors_Feb2022_V3.

  • True
  • False

Q4. Foldering may be used by data analysts to organize folders into what?

  • Databases
  • Subfolders
  • Versions
  • Tables

Q5. Data analysts use archiving to separate current from past work. What does this process involve?

  • Reviewing current data files to confirm they’ve been cleaned
  • Moving files from completed projects to another location
  • Reorganizing and renaming current files
  • Using secure data-erase software to destroy old files

Q6. Fill in the blank: Data analysts create _____ to structure their folders.

  • hierarchies
  • ladders
  • sequences
  • scales

Q7. A data analyst wants to ensure only people on their analytics team can access, edit, and download a spreadsheet. They can use which of the following tools? Select all that apply.

  • Sharing permissions
  • Encryption
  • Templates
  • Filtering

Q8. To reduce clutter, a data analyst hides cells that contain long, complex formulas. To view the formulas again, the analyst will need to adjust the spreadsheet sharing or encryption settings.

  • True
  • False

Prepare Data for Exploration Week 05 Quiz Answers

Practice Quiz-1 Answers

Reviewing the data enables you to describe how you will use it to achieve your client’s goals. First, you notice that all of the data is first-party data. What does this mean?

  • It’s subjective data that measures qualities and characteristics.
  • It’s data that was collected by Garden employees using their own resources.
  • It’s a type of data that’s categorized without a set order.
  • It’s data that was collected from outside sources.

Q2. Next, you review the customer satisfaction survey data:

CustomerSurveyData – Customer survey data.csv

The question in column E asks, “Was your order accurate? Please respond yes or no.” What kind of data is this?

  • Clean data
  • Ordinal data
  • Second-party data
  • Boolean data

Q3. Now, you review the data on delivery times and the distance of customers from the restaurant:

DeliveryTimes_DistanceData – Delivery times_distance.csv

The data in column E shows the duration of each delivery. What type of data is this? Select all that apply.

  • Quantitative data
  • Qualitative data
  • Discrete data
  • Continuous data

Q4. The next thing you review is the file containing pictures of sandwich deliveries over a period of 30 days. This is an example of structured data.

  • True
  • False

Q5. Now that you’re familiar with the data, you want to build trust with the team at Garden.

What actions should you take when working with their data? Select all that apply.

  • Keep the data safe by implementing data-security measures, such as password protection and user permissions.
  • Organize the data using effective naming conventions.
  • Share the client’s data with other delivery restaurants to compare performance.
  • Post on social media that you’re working with Garden and would like feedback from any of your contacts who have ordered there before.

Q6. Consider and respond to the following question. Select all that apply.

Our data analytics team often surveys clients to get their feedback. If you were on the team, how would you ensure the results do not favor a particular person, group of people, or thing?

  • Instruct participants to share their name and contact information.
  • Ensure the survey sample represents the population as a whole.
  • Make sure the wording of the survey question does not encourage a specific response from participants.
  • Give participants enough time to answer each survey question.

Q7. Consider and respond to the following question. Select all that apply.

Our data analytics team often uses both internal and external data. Describe the difference between the two.

  • Internal data lives within a company’s own systems. External data lives outside the organization.
  • External data is typically generated from within the company. Internal data is generated outside the organization.
  • Internal data is typically generated from within the company. External data is generated outside the organization.
  • External data lives within a company’s own systems. Internal data lives outside the organization.

Q8. Consider and respond to the following question. Select all that apply.

Our analysts often work with the same spreadsheet, but for different purposes. How would you use filtering to help in this situation?

  • Use filters to highlight the header row
  • Use filters to simplify a spreadsheet by only showing you only the information you need.
  • Use filters to sort the data in a meaningful order
  • Use filters to show only the data that meets a specific criteria while hiding the rest

Q9. Next, your interviewer wants to better understand your knowledge of basic SQL commands. He asks: How would you write a query that retrieves only data about people with the last name Hassan from the Clients table in our database?

  • SELECT DATA FROM Clients WHERE ‘Hassan’
  • SELECT Clients WHERE Last_Name= ‘Hassan’ FROM *
  • SELECT * FROM Clients WHERE Last_Name= ‘Hassan’
  • SELECT All WHERE Last_Name ‘Hassan’ FROM Clients

Q10. For your final question, your interviewer explains that Sewati Financial Services cares about its clients’ trust, and this is an important responsibility for the data analytics team. They do this by:

  • protecting clients from unauthorized access to their private data
  • ensuring freedom from inappropriate use of client data
  • giving consent to use someone’s data

He asks: Which data analytics practice does this describe?

  • Encryption
  • Data privacy
  • Sharing permissions
  • Bias

Next Course Quiz Answers >>

Ask Questions to Make Data-Driven Decisions

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Foundations: Data, Data, Everywhere

All Course Quiz Answers of Google Data Analytics Professional Certificate

Course 01: Foundations: Data, Data, Everywhere

Course 02: Ask Questions to Make Data-Driven Decisions

Course 03: Prepare Data for Exploration

Course 04: Process Data from Dirty to Clean

Course 05: Analyze Data to Answer Questions

Course 06: Share Data Through the Art of Visualization

Course 07: Data Analysis with R Programming

Course 08: Google Data Analytics Capstone: Complete a Case Study

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