1. A data analyst wants to create a
visualization that demonstrates how often data values fall into certain ranges.
What type of data visualization should they use?
Answers
·
Line
graph
·
Scatter
plot
·
Histogram
·
Correlation
chart
Explanation: Histograms are an
efficient tool for visualizing the shape of the distribution, finding key
patterns, and comprehending the dispersion of data. Data analysts who are
looking for insights into the frequency distribution of a continuous variable
will find them useful since they give a clear depiction of how data is
dispersed over various ranges.
2. What do correlation charts reveal
about the data they contain?
Answers
·
Causation
·
Relationships
·
Changes
·
Visualization
Explanation: The strength and direction
of the association between two or more variables in a dataset may be shown
clearly via the use of correlation charts. These charts are especially helpful
for gaining an understanding of the relationship between changes in one variable
and changes in another one.
3.
You are creating a presentation for stakeholders and are choosing whether to
include static or dynamic visualizations. Describe the difference between
static and dynamic visualizations.
Answers
·
Static
visualizations are interactive and can automatically change over time. Dynamic
visualizations do not change over time unless they’re edited.
·
Static visualizations do not change over time
unless they’re edited. Dynamic visualizations are interactive and can
automatically change over time.
·
Static
visualizations combine multiple visualizations into a whole. Dynamic
visualizations separate out the individual elements of a single visualization.
·
Static
visualizations separate out the individual elements of a single visualization.
Dynamic visualizations combine multiple visualizations into a whole.
4.
Sophisticated use of contrast helps separate the most important data from the
rest using the visual context that our brains naturally respond to.
Answers
·
True
·
False
5.
Design thinking is a process used to solve complex problems in a visually
appealing way.
Answers
·
True
·
False
Explanation: Not even close! Empathy
and a grasp of the requirements of the users are at the heart of design
thinking, which focuses on finding solutions to complicated issues in a manner
that prioritizes people. The visual appeal may come later when you're presenting
your solution, but the focus should actually be on resolving the problems that
real people are experiencing.
6.
Fill in the blank: During the _____ phase of the design process, you start to
generate data visualization ideas.
Answers
·
empathize
·
ideate
·
test
·
define
Explanation: During the phase of the
design process known as "ideation," when you first begin to produce
ideas, one of those phases is when you will focus on data visualization. At
this stage of the creative process, known as "brainstorming," possible
outcomes are investigated, and ideas begin to take form.
7. A data analyst adds labels to
their line graph to make it easier to read even though they already have a
legend on their visualizations. How does labeling the data make it more
accessible?
Answers
·
Labeling doesn’t depend on interpreting colors
·
Labelling
adds contrast to a visualization
·
Labeling
creates more visual interest
·
Labeling
helps redirect focus from outliers
Explanation: It is possible to make
data more easily understood by labeling it directly on a line graph for a few
different reasons. First, it eliminates the need that the viewer continually
look at a separate legend, which makes the information more simpler and clearer
to comprehend right away. In addition to this, it establishes a direct
relationship between the data points and the labels that correlate to them,
which contributes to an increased level of clarity. People who have trouble
understanding the legends or differentiating between the many colors on the
graph may benefit tremendously from this, as it may be of great assistance to
them. Labeling, in its most basic form, is one of the factors that helps to
make the data visualization experience more inclusive and user-friendly.
8. Fill in the blank: You should
distinguish elements of your data visualization by _____ the foreground and
background and using contrasting colors and shapes. This makes the content more
accessible.
Answers
·
highlighting
·
separating
·
overlapping
·
aligning
Explanation: You should differentiate
the pieces in your data visualization by adjusting the foreground and
background, using colors and forms that contrast with one another, and
manipulating the order of the items. This makes the material easier to reach by
increasing its visibility and assisting in the distinction of different pieces
included within the display.
9.
A data analyst working for an e-commerce website creates the following data
visualization to present the amount of time users spend on the site:
What type of visualization is this?
Answers
·
Correlation
chart
·
Histogram
·
Line
graph
·
Scatterplot
10.
A data analyst is creating a chart for a presentation. The data they will
display shows a correlation between variables. Why should they be careful when
presenting their chart to an audience?
Answers
·
Correlation can be misunderstood as causation.
·
Correlation
causes accessibility issues.
·
Correlation
should be avoided in charts.
·
Correlation
can only be represented in bar charts.
Explanation: It is important for a data
analyst to use caution when presenting a chart that demonstrates a connection
between variables since correlation does not always indicate causation. It is
essential to convey the message that the correlation of two variables does not
always imply that one variable causes the other variable. Jumping to
conclusions may result in misunderstandings or incorrect interpretations of
what was said or done, since there may be other variables at play. It is
possible to increase the likelihood that the audience will accurately draw
inferences from the information that is provided if context is provided, it is
made clear what the limits of the data are, and an emphasis is placed on
correlation rather than causation.
11. What type of data
visualizations allow users to have some control over what they see?
Answers
·
Aesthetic
visualizations
·
Dynamic visualizations
·
Geometric
visualizations
·
Static
visualizations
Explanation: Users are given some
degree of control over the information that is shown in interactive data
visualizations. Users are able to edit and examine the data depending on their
own tastes and areas of interest thanks to these representations. Users are
given the ability to zero in on certain facets of the data or to personalize
the presentation in accordance with their requirements by virtue of features
like as zooming, panning, filtering, and interactive components. Examples of
this kind of visualization include interactive charts, maps, and dashboards.
These types of visualizations provide users the ability to dynamically interact
with the information being shown, which makes the visualization more
interesting and user-centric.
12.
Design thinking is a process used to solve problems in a user-centric way.
Answers
·
True
·
False
Explanation: Without a doubt! When it
comes to finding solutions to problems, design thinking is all about making the
end user the focal point of attention. Empathy, ideation, prototyping, and
testing are all necessary steps in the process of developing solutions that
satisfactorily address the requirements of the users. This method focuses on
people rather than technology and uses an iterative process that fosters
innovative thinking and teamwork.
13.
During which phase of the design process do you try to understand the emotions
and needs of your target audience?
Answers
·
Prototype
·
Ideate
·
Test
·
Empathize
Explanation: During the empathy phase
of the design process, one of the primary focuses is on gaining an
understanding of the feelings and requirements of the target audience. During
this phase, you will do research and analysis to get insights into the
experiences, viewpoints, and difficulties faced by users. The designers may
have a better knowledge of the users' goals and requirements if they put
themselves in the consumers' shoes by empathizing with them, which in turn
guides the remainder of the design process.
14.
A data analyst wants to make their visualizations more accessible by adding
text explanations directly on the visualization. What is this called?
Answers
·
Distinguishing
·
Subtitling
·
Labeling
·
Simplifying
Explanation: The practice of adding
written explanations right on top of a graphic in order to make it easier to
understand is often known as "annotations." The viewer is able to get
a deeper comprehension of the data that is being given with the assistance of
annotations, which provide more context, information, or insights right on the
visual components. This method both improves clarity and guarantees that
viewers can appropriately perceive the information that is being presented to
them.
15.
What should data analysts do to make presentations more accessible for people
who are blind and people with low vision?
Answers
·
Minimize
contrast between colors
·
Remove
labels from data
·
Provide text alternatives
·
Avoid
using shapes and patterns to differentiate data
16.
You need to create a chart that displays the number of data records in each age
group of a dataset. What type of chart would best represent this data?
Answers
·
Histogram Chart
·
Ranked
Bar Chart
·
Correlation
Chart
·
Time
Series Chart
Explanation: To graphically display the
range of ages covered by each set of data records, either a bar chart or a
histogram would be an appropriate option. Both the x-axis, which may represent
the various age categories, and the y-axis, which can show the total number of
data records, can be used. The amount of records that fall inside a certain age
range will be represented by each individual bar or bin. The information may be
quickly compared and comprehended by viewers thanks to the use of a chart like
this one, which displays the data distribution in an accurate manner across
various age groups.
17.
Which of the following is generally good practice when using bar charts?
Answers
·
Display
the bars in ranked order
·
Make
the gaps wider than the bars.
·
Design
bar charts with a single color.
·
Avoid
stacked bar charts.
Explanation: Always make sure that the
scale on the axis of your bar chart is legible and consistent. Because of this,
it is guaranteed that viewers will have the ability to correctly evaluate the
height of the bars and draw meaningful comparisons across the various categories.
Scales that are not consistent with one another may be deceiving and may cause
one to misunderstand the facts. Make sure that the scale is clearly identified
and that it is applied uniformly across all relevant bars, regardless of
whether you are using the y-axis to indicate counts, percentages, or another
kind of measurement.
18.
What are the key elements of effective visualizations you should focus on when
creating data visualizations? Select all that apply.
Answers
·
Clear meaning
·
Sophisticated use of contrast
·
Visual
form
·
Refined
execution
19.
Fill in the blank: Design thinking is a process used to solve complex problems
_____.
Answers
·
as
quickly as possible
·
in a user-centric way
·
using
a set order of processes
·
with
minimal user input
20.
Fill in the blank: A data analyst can make their visualizations more accessible
by adding _____, which are text explanations placed directly on the
visualizations.
Answers
·
labels
·
legends
·
callouts
·
subheadings
Explanation: Annotations are written
explanations that are put right on the visuals; when a data analyst adds
annotations to their visualizations, they make the visualizations more
accessible to the audience.
21. Distinguishing
elements of your data visualizations makes the content easier to see. This can
help make them more accessible for audience members with visual impairments.
What are some methods data analysts use to distinguish elements?
Answers
·
Ensure
all elements are highlighted equally
·
Separate the foreground and background
·
Use
similar colors and shapes
·
Add
a legend
22.
You need to create a chart that explores how temperature changes throughout the
year. What type of chart would best represent this data?
Answers
·
Correlation
Chart
·
Time
Series Chart
·
Histogram
·
Ranked
Bar Chart
Explanation: For the purpose of
depicting how the temperature changes over the course of a year, either a line
chart or a time series chart would be an appropriate option. These kinds of
charts often feature time on the x-axis (months or days), and temperature on
the y-axis, which enables you to visually analyze the trend as well as the
changes in temperature over a certain time period. The temperature swings that
occur over the course of a year are effectively shown by the line that connects
all of the data points.
23. What type of visualizations give
you the most control over the story you want to tell with your data?
Answers
·
Static visualizations
·
Dynamic
visualizations
·
Aesthetic
visualizations
·
Geometric
visualizations
Explanation: Dashboards and other
interactive representations of data allow you the greatest amount of control
over the narrative you want to convey using the information you have collected.
Dashboards provide a complete picture of the data by combining numerous visualizations,
charts, and graphs in a single interface. This is made possible by the fact
that dashboards may mix these elements. You have the ability to lead your
audience through the data by using interactive tools such as filtering,
highlighting, and drill-down choices. These elements provide your audience the
opportunity to investigate certain facets and derive significant insights. This
amount of control boosts your ability to personalize the narrative and ensures
that the audience connects with the data in a manner that is congruent with the
story you want to portray. In addition, this level of control enables you to
better regulate the flow of the presentation.
24.
Fill in the blank: When choosing a chart you should choose the one that _____.
Answers
·
makes
use of the most modern visualization tool
·
uses
the least number of visual elements like size and shape
·
uses
as many visual elements like size and shape as possible
·
makes it easiest to understand the point you are trying to make
Explanation: When selecting a chart,
you should go with the one that conveys the desired message most clearly and
accurately while also providing the clearest representation of the connections
or patterns in your data.
25.
A data analyst is designing a chart. They decide to use colors that make sense
to their audience. What phase of creating data visualizations does this
describe?
Answers
·
Test
Phase
·
Ideate
Phase
·
Prototype
Phase
·
Empathize Phase
Explanation: During the design or
formatting step of the process of developing data visualizations, a choice must
be taken on the colors to use so that they are meaningful to the target
audience. During this stage of the process, the data analyst takes into account
the visual aesthetics, such as the choice of colors, to ensure that the chart
is visually appealing and successfully conveys the information to the target
audience.
26.
During which phase of the design process do you start to generate data
visualization ideas?
Answers
·
Ideate
·
Test
·
Empathize
·
Define
Explanation: During the phase of the
design process known as "ideation," when you first begin to produce
ideas, one of those phases is when you will focus on data visualization. This
stage is characterized by creative brainstorming and the investigation of a
variety of alternative ideas in order to properly communicate the information.
down this essential stage of the design thinking process, you will examine a
wide range of options and methods before zeroing down on the concepts that
provide the greatest potential for success.
27.
What should you include in the headline of a data visualization?
Answers
·
Abbreviations
·
Clear language
·
Acronyms
·
Fancy
typography
Explanation: A headline for a data
visualization should clearly and concisely describe the primary takeaway or
insight that the visualization is meant to convey to the audience. It need to
give a summary that is both clear and succinct of the most important takeaway from
the data. Since the title is often the first thing that visitors see, it is
important that it grabs their attention and is pertinent to the information
that is being provided in the visualization. It is a method for directing the
understanding of the audience and establishing the context for the purpose of
comprehending the facts.
28.
A data analyst is making their data visualization more accessible. They
separate the background and the foreground of the visualization using bright,
contrasting colors. What does this describe?
Answers
·
Labelling
·
Text
alternatives
·
Distinguishing
·
Text-based
format
Explanation: The use of colors that are
strikingly different from one another in order to differentiate between the
foreground and backdrop of a data visualization is referred to as color
contrast or color differentiation. This method increases visibility and makes it
simpler for everyone, particularly those who have visual impairments, to
differentiate between the many components that are being shown. It is an
approach that is used with the goal of enhancing the accessibility of the
visualization as a whole by ensuring that it is clear and legible.
29.
Causation occurs when an action directly leads to an outcome.
Answers
·
True
·
False
Explanation: Without a doubt! The
concept of causation refers to the link between an event, known as the cause,
and another event, known as the effect, in which the occurrence of the cause
directly leads to the occurrence of the effect. It suggests that one variable has
a direct and, quite frequently, observable impact on another one. The ability
to correctly analyze and comprehend the connections between variables requires
a solid foundation in the concept of causality.
30.
What type of charts are effective for presenting the composition of data?
Select all the apply.
Answers
·
Pie chart
·
Line
chart
·
Tree
map
·
Heat
map
31. When using design
thinking, what group of people should you think about the most?
Answers
·
The
general public
·
Your
team
·
The
shareholders
·
Your users
Explanation: When using design
thinking, the primary focus should be on the people who will ultimately utilize
the product, often known as the end-users or customers. Design thinking is a
human-centered approach that places a priority on knowing the requirements, preferences,
and past experiences of the people who will eventually use the product,
service, or solution that is being produced or who will be influenced by it.
Empathy for the people who will be using the product is one of the fundamental
tenets of design thinking. Involving consumers at every stage of the design
process helps to guarantee that the resulting solutions are applicable,
efficient, and easy to understand and use.
32.
You are in the ideate phase of the design process. What are you doing at this
stage?
Answers
·
Making
changes to their data visualization
·
Generating
visualization ideas
·
Creating
data visualizations
·
Sharing
data visualizations with a test audience
Explanation: During the part of the
design process known as ideate, you will be engaged in creative brainstorming
and coming up with a variety of different concepts. In this stage of the
process, you will investigate a variety of potential answers to the issue at
hand. It entails supporting a free flow of ideas without immediately judging
them, which makes room for creative thinking and the investigation of a number
of different alternatives. Before going on to the subsequent stages of the
design process, it is important to first generate a large number of different
ideas for prospective solutions.
33.
Where is the best place to put labels that describe the meaning of individual
data elements in a data visualization?
Answers
·
Left
of the chart area
·
In
the legend
·
In the data
·
Below
the chart area
34.
Fill in the blank: A data analyst creates a presentation for stakeholders. They
include _____ visualizations because they don’t want the visualizations to
change unless they choose to edit them.
Answers
·
aesthetic
·
dynamic
·
static
·
geometric
Explanation: A presentation for several
stakeholders is crafted by a data analyst. They include visuals that are static
since they do not want the visualizations to alter unless they manually make
such changes.
35.
While creating a chart to share their findings, a data analyst uses the color
red to make important data stand out and separate it from the rest of the
visualization. Which element of effective visualization does this describe?
Answers
·
Refined
execution
·
Clear
meaning
·
Sophisticated
use of contrast
·
Subtitles
36.
You are in the process of creating data visualizations. You have considered the
goal, the audience's needs, and come up with an idea. Next, you will share the
visualization with peers. What phase of the design process will you be in?
Answers
·
Ideate
·
Define
·
Test
·
Empathize
37.
What text element in a visualization should be placed above the chart and
clearly state what data is being presented?
Answers
·
Headline
·
Label
·
Annotation
·
Subtitle
Explanation: Each data visualization
should include a title, which should not exceed two lines of text in length.
Titles should be provided. A title should provide a general overview of the
information that is shown in a data visualization without drawing attention to
specific patterns or standouts in the data. The titles of visualizations should
be placed either right above or immediately next to the element they describe.
38.
How much data should you represent when designing an effective data
visualization?
Answers
·
Include
a subset of the data that your audience will like
·
Only
represent data that supports your initial hypothesis
·
Include
all of the data from your analysis to ensure that your data visualization is
complete and accurate
·
Only represent data the audience needs to
understand your findings, unless it is misleading
39.
A data analyst creates a histogram to share in a presentation. What are
histograms used to demonstrate?
Answers
·
How
two or more values contrast and compare
·
How
much each part of something makes up the whole
·
How
data has changed over time
·
How
often data values fall into certain ranges
40.
What can you do to simplify your visualizations to make them accessible to a
broad audience?
Answers
·
Use
more text than visuals
·
Remove
data labels
·
Reduce
the amount of information
·
Use
abbreviations in headlines
41. Fill in the blank: A data analyst creates a presentation
for stakeholders. They include _____ visualizations because the analyst wants
the presentations to be interactive and automatically change over time.
Answers
·
dynamic
·
aesthetic
·
geometric
·
static