Data Visualization and Communication with Tableau Quiz Answers

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Week 01: Data Visualization and Communication with Tableau Quiz Answers

Quiz 1: Week 1 Quiz

Q1. According to the data analytics company Gartner, the majority of companies reported the reason their big data projects failed is due to:

organizational failures only
mostly organizational failures, but also some technical failures
mostly technical failures, but also some organizational failures
equal parts organizational and technical failures

Q2. True/False: Everybody in the analytics world agrees that your job as a data analyst is to ask and answer the one, true, right question.

True
False

Q3. In this course, we used the S.M.A.R.T acronym to refer to goals that are:

Strategic, Measurable, Attainable, Relevant, and Time-bound
Specific, Measurable, Active, Realistic, and Time-bound
Specific, Measurable, Attainable, Relevant, and Time-bound
Specific, Measurable, Attainable, Realistic, and Time-bound

Q4. Which of the following steps of the analytics project life cycle should you complete first?

Making a dashboard
Defining a SMART goal
Analyzing data
Making a data analysis plan

Q5. True/False: Including the business metric that you will use to assess success in your business analytics project will make your project goal sufficiently specific to ensure success.

True
False

Q6. Which of the SMART criteria are NOT met by this data analytics project goal (pay close attention to whether the options are words the SMART acronym stands for)?

The goal of this project is to, within 45 days, use the inventory, production, and customer service databases from national manufacturing plants to reduce the number of polo shirts returned for manufacturing defects.

Attainable
Specific
Time-bound
Measurable
Reasonable

Q7. True/False: Stakeholders are those individuals who are influenced by the outcome of your project or who might have a strong interest in it.

True
False

Q8. Elicitation sessions occur:

Before you have accepted an analysis job
after you have accepted an analysis job, and should conclude mid-way through a data analysis
after you have accepted an analysis job, and should conclude before you begin a data analysis
after you have accepted an analysis job, and should continue throughout the life cycle of a data analysis project

Q9. You are an analyst at a bank. Your bank ran a short-term experiment in which they provided credit cards to a wider range of applicants than normal, including applicants whose applications would typically be rejected due to their troubled financial profiles. Your job is to model the data from this experiment to create a decision-making algorithm that will help the bank decide how to respond to future credit card applications more profitably.

The following parties are NOT likely to be key stakeholder(s) in your project (select all that apply):

The bank’s creditors
The bank, itself
The bank’s shareholders
Individuals who will apply for credit cards in the future.
Individuals who applied for credit cards in the past, but were denied

Q10. At the beginning of any data analysis project, you should meet with your key stakeholders to understand:

what problem the business is experiencing that stakeholders hope to solve.
whether all the stakeholders agree about what business problem needs to be solved.
what types of effects or factors you should be considering in your data analysis.
what kinds of analytic tools and results the company culture will be open to.
all of the above.

Q11. According to Doug Laney, VP of Information Innovation and Strategy at Gartner, why don’t more companies move higher on the analytics continuum? (Check all that apply)

Inertia (comfort with the way businesses did things in the past)
The financial burden of implementing more sophisticated data analytics is too high
Decision-makers view analytic analyses as “black boxes” they don’t understand
Implementing analytic solutions higher up on the analytics continuum would require hiring more skilled employees than the company could accommodate

Q12. True/False: When you are designing your business analysis plan, you should treat your business metric as the independent variable in your data analysis.

True
False

Q13. SPAPs should be altered after you begin a data analysis.

True
False

Q14. How many layers should there be in the “independent variables” section of your pyramid?

2
3
4
As many layers and sub-layers as needed to cover all the issues you want to be sure you document or address

Q15. The best charts for assessing the categories and subcategories listed in the intermediate layers of your SPAP include (select all that apply):

Bar charts
Scatter plots
Pie charts
Line charts

Week 02: Data Visualization and Communication with Tableau Quiz Answers

Q1. Use the Dognition_aggregated_by_DogID data set for the quiz questions. Note that we use comma (,) to separate groups of thousands in numbers.

How many unique human user IDs are there in the Dognition_aggregated_by_DogID data set?

14,433
16,261
17,985
17,986
None of the above

Q2. What feature is common to all the rows that have a value of 37 in the “State” field of the Dognition_aggregated_by_DogID data set? Check all that apply.

They are all from Estonia
They are all “charmers”
They are all golden retrievers
They all completed 37 tests
They all weigh 37 pounds

Q3. What property is common to almost all the data points that had “Sign In Counts” of greater than 175 in the Dognition_aggregated_by_DogID data set?

They all have an Einstein profile
They are all from the city of Saint Jean de Monts
They are all from Estonia
They all have Dog ID fd51b784-7144-11e5-ba71-058fbc01cf0b
They are all Shih Tzus that weigh 190 lbs

Q4. The Personality Dimension that has the highest average number of completed tests in the Dognition_aggregated_by_DogID data set is clear:

The Expert Dimension
The Socialite Dimension
The Renaissance Dimension
The Protodog Dimension
None of them. All of the personality dimensions have very similar completion rates.

Q5. In the Dognition_aggregated_by_DogID data set, what is consistent about the relationship between the breeding group and the number of tests completed, regardless of whether you aggregate the variable representing the number of tests completed by the median or the average of the breeding group?

Herding dogs finish the greatest number of tests
Sporting dogs finish the greatest number of tests
Toy dogs complete the least number of tests
Hound dogs complete the least number of tests
None of the above

Q6. In the Dognition_aggregated_by_DogID data set, what personality type has the strongest representation (greatest number of records) in the sporting breed group?

Socialite
Charmer
Protodog
Expert
Einstein

Q7. In the Dognition_aggregated_by_DogID data set, which of the following describes the median number of tests dogs of different breed types complete?

Cross-breed dogs complete a median of 8 tests, while all the other breed types complete a median of 7 tests
All breed types complete a median of 5 tests
All breed types complete a median of 7 tests
Pure-breed dogs complete a median of 8 tests, while all the other breed types complete a median of 7 tests
Popular-Hybrid dogs complete a median of 8 tests, while all the other breed types complete a median of 7 tests

Q8. In the Dognition_aggregated_by_DogID data set, how does the average number of tests dogs complete compare for fixed vs. not fixed dogs across different breed types? Click all that apply

The greatest difference between the average number of tests completed by fixed vs. non-fixed dogs occurs in the Mixed Breed/ I Don’t Know breed category
Fixed dogs complete more tests than non-fixed dogs in all breed types
Fixed dogs complete more tests than non-fixed dogs in the Cross-Breed and Mixed Breed/ I Don’t Know breed categories, but not in the other breed categories
Fixed dogs complete fewer tests than non-fixed dogs in all breed types
Fixed dogs complete fewer tests than non-fixed dogs in the Cross-Breed and Mixed Breed/ I Don’t Know breed categories, but not in the other breed categories

Q9. In the Dognition_aggregated_by_DogID data set, which of the following are true about the average number of tests dogs complete when comparing DNA vs. not DNA-tested dogs who were fixed vs. not fixed across different breed types? Click all that apply.

The Cross-Breed dogs that were DNA tested but NOT fixed were mostly Golden Doodles
DNA-tested dogs completed more tests than dogs that were NOT DNA tested in all categories except for the category of Popular Hybrids that were fixed
There was only one dog in the Popular Hybrid breed category who was DNA tested but not fixed
DNA-tested dogs completed fewer tests than dogs that were NOT DNA tested in all categories except for the category of Popular Hybrids that were fixed
The Cross-Breed dogs that were DNA tested but NOT fixed were mostly Labrador Retriever-Golden Retriever Mixes

Q10. In the Dognition_aggregated_by_DogID data set, when you make a filled map that displays the number of unique Dog IDs in each country, there is a country in Africa that has a deep color, suggesting it has a lot of users. When you hover over that country, what Country is displayed on the tooltip?

AR
NO
SA
ZA
N/A

Q11. In the Dognition_aggregated_by_DogID data set, which state within the United States has the most Dognition customers?

Florida, with Texas having the second greatest number of customers
Texas, with California having the second greatest number of customers
North Carolina, with New York having the second greatest number of customers
California, with New York, has the second-greatest number of customers
North Carolina, with California having the second greatest number of customers

Q12. In the Dognition_aggregated_by_DogID data set, dogs in which of the following states did customers complete a median number of tests that were greater than 13? Check all that apply.

Maine (ME)
North Carolina (NC)
North Dakota (ND)
South Dakota (SD)
Wyoming (WY)

Q13. Which of the following is true?

Average and median aggregations are equally sensitive to outliers
Average aggregations are more sensitive to extreme values than median aggregations
Median aggregations are more sensitive to extreme values than average aggregations
Neither average nor median aggregations are sensitive to outliers

Q14. In the Dognition_aggregated_by_DogID data set, when looking at only dogs who completed 19 or fewer tests, which of the following is true about the relationship between inter-test intervals (ITIs) and number of tests completed? Click all that apply.

There was a non-significant negative (p > .05) correlation between average ITIs and number of tests completed
There was a significant positive (p < .05) correlation between median ITIs and the number of tests completed
There was a significant negative (p < .05) correlation between median ITIs and the number of tests completed
There was a non-significant positive (p > .05) correlation between average ITIs and the number of tests completed
There was a significant positive (p < .05) correlation between average ITIs and the number of tests completed

Q15. In the Dognition_aggregated_by_DogID data set, when looking at only dogs who completed 7 or fewer tests, which of the following is true about the relationship between inter-test intervals (ITIs) and number of tests completed? Click all that apply

There was a non-significant negative (p > .05) correlation between average ITIs and number of tests completed
There was a significant positive (p < .05) correlation between median ITIs and the number of tests completed
There was a significant positive (p < .05) correlation between average ITIs and the number of tests completed
There was a significant negative (p < .05) correlation between median ITIs and the number of tests completed
There was a non-significant positive (p > .05) correlation between average ITIs and the number of tests completed

Week 03: Data Visualization and Communication with Tableau Quiz Answers

Q1. Use the dognition_data_no_aggregation data set provided in this course for this quiz.

In the dognition_data_no_aggregation data set, the greatest drop-offs of test-takers occur after a subcategory of tests is completed rather than while the subcategories of tests are still in progress.

True
False

Q2. In the dognition_data_no_aggregation data set, after which game is the drop-off of completed tests the greatest?

Inferential Reasoning Game
Cunning Game
Yawn Game
Memory vs. Pointing Game
Eye Contact Game

Q3. If you remove all the entries associated with Shih Tzu dogs that weigh 190 pounds from the dognition_data_no_aggregation data set, how many different sequences of tests were administered to customers in the data that are left?

1
2
3
at least 4
at least 15

Q4. During which day of the week do customers play Dognition games the most?

Wednesday
Thursday
Friday
Saturday
Sunday

Q5. During which month in the data set were the most tests completed?

August 2013
March 2014
October 2014
June 2015

Q6. After adjusting the time stamps of the tests completed by United States users provided in the “Created At” field of the dognition_data_no_aggregation data set for time zone differences, during which hour of the day do Dognition customers play the most amount of games?

7 AM
noon
3 PM
7 PM
10 PM

Q7. In the dognition_data_no_aggregation data set, approximately what percentage of users who begin taking the Dognition Assessment complete 20 tests?

Q8. In the dognition_data_no_aggregation data set, what percentage of users who begin taking the Dognition Assessment using a “Free Start” promotion complete 20 tests?

Q9. Using the dognition_data_no_aggregation data set, if you make a table using the “Dog ID” and “Test Name” variables on the rows shelf, and Created At on the Text property of the Marks card, which of the following might be a value you would see in the column farthest to the right, if the “Created At” pill was blue and read SECOND(Created At)?

2/8/2013 1:39:00 AM
0
39
1:39:00 AM

Q10. If you were writing a calculation to rank each test a dog completed by its time stamp in the dognition_data_no_aggregation data set, what would be missing from the following version of your rank table calculation: RANK(([Created At]),’asc’)

an aggregation before [Created At], the most appropriate of which is MEDIAN
an aggregation after [Created At], the most appropriate of which is MEDIAN
an aggregation before [Created At], the most appropriate of which is ATTR
an aggregation after [Created At], the most appropriate of which is ATTR
There is nothing missing

Q11. You are writing a calculation to rank each test a dog completed by its time stamp in the dognition_data_no_aggregation data set. You’ve configured your table calculation so that “Dog ID” and “Test Name” are in the Partitioning field and “Second Created” is in the Addressing field. The resulting rank will:

Provide one number for every test within a subcategory
List “1” for the first test of every Dog ID
Provide one correctly ranked number for every test within a single Dog ID
Provide one incorrectly ranked number for every test within a single Dog ID

Q12. You are writing a calculation to include a column in a table that ranks each test a human user completed by its time stamp in the dognition_data_no_aggregation data set. You put this column directly to the left of the column you made to rank each test a dog completed by its time stamp. The following field(s) will go in the Partitioning field in the calculation configuration page in your new calculation meant to rank each test a human user completed: (check all that apply)

Created At

Dog ID
Test Name
User ID
None of the above

Week 04: Data Visualization and Communication with Tableau Quiz Answers

Q1. The hourglass model for structuring effective business presentations suggests you should:

Begin your presentation with motivating context and end with your business recommendation
Begin and end your presentation with motivating context
Begin your presentation with your agenda and end with a summary of what you covered
Begin your presentation with your agenda and end with a story

Q2. Beginning your business presentation in the middle of the plot of a motivational story can sometimes be an effective way to lead into your business recommendation.

True
False

Q3. The storyboarding process includes:

asking for feedback
determining the precise order in which the scenes will be organized
choosing the best visualizations to communicate the information about each scene
narrowing in on the minimum number of scenes necessary to convey your data story
All of the above

Q4. According to the psychology literature, if the business recommendation you are going to make in a business presentation is likely to be controversial, you should order the stem of your presentation hourglass so that the:

the least controversial point is presented first.
The least complicated story point is presented first.
strongest story point is presented first.
most emotional story point is presented first.

Q5. As a data analyst, you can avoid the logical fallacy of overgeneralization by:

insisting that you are given a very large data set to analyze.
selecting a small, unbiased sample.
ensuring the data you work with is a selected subset with a strong data story.
None of the above

Q6. To test whether a certain advertising campaign would work, an analytics team sorts their customer list from lowest to highest customer ID number and then sends their advertisement to the first 1000 customers on the list. The rest of the customers did not receive any advertisements that week. When analyzing the results of the campaign one week later, the analytics team realized that there was a previously unknown pattern in the customer ID numbers: the lower the customer number, the longer the person had been a customer. Thus, the customers who received the advertisement were the individuals who had been customers with the company the longest. The analytics team decided the test was invalid and needed to be repeated. The reason for their decision was that analyzing the results in their current form would result in the following logical fallacy (or fallacies):

Over-generalization
Inferring causation from correlation
Lack of controls
All of the above
None of the above

Q7. When two variables are correlated, one variable does not cause the other variable.

True
False

Q8. When tests can’t be run, which of the following can data analysts do to assess the degree of confidence one should have in the nature of a correlation between two variables? Choose all that apply.

Identify different but complementary ways to use the same data set to assess the causal relationship about which you are hypothesizing.
Infer that if the observed effect is extremely large or obvious, it is likely real.
Attempt to replicate the effect by examining whether the correlation on which you are basing your business recommendation exists in other data sets or contexts.
Assess whether there are additional variables that can explain the relationship.

Q9. Which of these charts would be the best way to display how Smartphone sales have changed over time?

Neither Chart A nor Chart B is effective
Chart B
Chart A
Chart A and Chart B are equally effective

Q10. When you want to represent very detailed and nuanced information about continuous variables, given humans’ ability to perceive relative differences along different kinds of visual attributes, which of the following attributes should you exploit in your visualizations? Choose the best 2 options.

Area
Color
Length
Volume
Position

Q11. If you are in a situation where you MUST use color bars to represent detailed information about a continuous variable, you should:

use colors that are very bright so that they can easily be detected.
use a gray scale that goes from black to white.
use a color bar that color-blind people can perceive.
use color bars that only have gradations from one color to a second color so that the audience isn’t distracted by excess color.

Q12. Visualizations for persuasion should: (Choose all that apply)

Show as much data as possible.
direct your audience’s eyes to the precise points of the data that support your argument.
show selected pieces of data.
show the visualizations in an order that helps your audience evaluate the options clearly.

Q13. Which of the following reflects (s) the principles of maximizing the data-ink ratio? Choose all that apply.

Reducing the amount of text on the slide
Making the borders of bars in a graph the same as the slide background
Including a bar at the bottom of the slide to indicate how far along you are in your presentation
Making the scales and labels of the graph easy to read

Q14. It’s a good idea to apply the rule of thirds to: (Choose all that apply)

Transition slides
Slides illustrating stories
Soft break slides
Slides meant to catch your audience’s attention
Slides containing data

Q15. Effective presentation techniques include:

keeping a physically open posture by keeping your arms away from the front of your body
facing your audience and looking at different people in the room
Being natural in your movements
refraining from looking down or reading your slides.
all of the above

Q16. A hospital was having problems with the amount of time employees with direct care responsibilities were absent from work. Due to the high levels of absenteeism, patient satisfaction was declining, 20% of patient-related work was not getting done, and 47% of nonpatient work was not getting done. At the advice of a consulting company, the hospital implemented a positive incentive system that would allow all employees to convert up to 24 hours of unused sick time into additional pay or more vacation days in order to reduce absenteeism. After 6 months of implementing the program, the hospital analysts calculated that absentee rates declined an average of 11.5 hours per employee, and concluded that the program was successful in this company. Did the hospital analysts commit any logical fallacies when arriving at their conclusion, and if so, which fallacy (or fallacies)?