1. A data analyst working for an e-commerce website creates the
following data visualization to show the amount of time users spend on the
site:
What type of visualization is it?
- Correlation chart
- Line graph
- Scatter plot
- Histogram
2. What do correlation charts reveal about the data they
contain?
- Relationships
- Changes
- Visualization
- Causation
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.
- Static visualizations separate out the individual
elements of a single visualization. Dynamic visualizations combine
multiple visualizations into a whole.
- Static
visualizations combine multiple visualizations into a whole. Dynamic
visualizations separate out the individual elements of a single
visualization.
- 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.
Explanation: It is
important to take into consideration the type of your data, the amount of
interaction that is necessary, and the narrative that you want to portray when
making a decision between static and dynamic visualizations for stakeholders.
It is possible that static graphics are better suitable for a presentation that
is clear and unchanging, but dynamic visuals have the potential to increase
engagement and provide stakeholders the opportunity to investigate the data on
their own.
4. What are the key elements of effective visualizations you
should focus on when creating data visualizations? Select all that apply.
- Visual form
- Sophisticated use of contrast
- Refined execution
- Clear meaning
5. Fill in the blank: Design thinking is a process used to solve
problems in a _____ way.
- analytical
- critical
- user-centric
- design-centric
Explanation: In
order to address challenges in a manner that is both creative and user-centric,
design thinking is a method that is used. It places an emphasis on empathy,
ideation, and prototyping in order to come up with new solutions that cater to
the requirements and preferences of the end-users.
6. Fill in the blank: During the _____ phase of the design
process, you start to generate data visualization ideas.
- test
- ideate
- empathize
- define
Explanation: When
you are in the ideation phase of the design process, you will begin to produce
ideas for data visualization strategies. During this stage of the creative
process, you will investigate a wide range of ideas and options from which you
will ultimately choose the visualization solutions that have the most
potential.
7. Fill in the blank: A data analyst can make their
visualizations more accessible by adding _____, which are text explanations
placed directly on the visualizations.
- callouts
- legends
- labels
- subheadings
Explanation: The
addition of annotations, which are textual explanations that are put right on
the visualizations, is one way for a data analyst to make their visualizations
more accessible to the public. For the purpose of providing context,
highlighting vital points, and guiding the viewer through the essential
components of the visualization, annotations are of great use. In particular,
they are an effective instrument for boosting comprehension, particularly for a
wide range of audiences.
8. 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 is a method data analysts use to
distinguish elements?
- Separate the
foreground and background
- Ensure all elements are highlighted equally
- Add a legend
- Use contrasting colors and shapes
Explanation: The
use of color contrast is one strategy that data analysts follow in order to
differentiate pieces in data visualizations with the purpose of improving
accessibility. This entails the use of colors that have a contrast that is both
obvious and distinct, which makes it simpler for persons who have visual
impairments to discriminate between various items, data points, or categories.
The readability of text is improved by a high color contrast, which also
guarantees that the information is clear and understandable for a wide range of
readers. When it comes to the creation of visualizations that are accessible
and inclusive, this is a crucial concern.
9. 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?
- Sophisticated use of contrast
- Clear meaning
- Refined execution
- Subtitles
Explanation: When
it comes to successful visualization, the element of emphasis is represented by
the use of the color red to draw attention to significant data and
differentiate it from the rest of the display. The act of emphasizing certain
aspects or data points in order to attract attention and communicate the
relevance of such aspects is known as emphasis. Creating emphasis and directing
the viewer's attention is a popular approach that involves the strategic use of
color. For example, making crucial data more colorful or distinguishable is one
example of this strategy. In this way, it helps to guarantee that the audience
is able to easily recognize the most important information.
10. 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?
- Histogram
- Line Graph
- Scatter Plot
- Correlation Chart
Explanation: The
usage of a histogram is something that a data analyst may use in order to
demonstrate how often data values fall into certain ranges. A histogram is a
graphical representation that illustrates the frequency of occurrences inside
each bin. It classifies data into bins or intervals and arranges them in a
hierarchical fashion. It simplifies the process of recognizing patterns,
trends, and the concentration of values within certain ranges by providing a
visual depiction of the distribution of the data.
11. A data analyst notices that two variables in their data seem
to rise and fall at the same time. They recognize that these variables are
related somehow. What is this an example of?
- Correlation
- Visualization
- Causation
- Tabulation
Explanation: As an illustration of correlation, consider the situation in
which two variables in the data experience simultaneous increases and
decreases, which indicates that there is a connection between them. In
statistical analysis, correlation is used to determine the degree of link or
dependency between two variables. Positive correlation is the term used to
describe the situation in which one variable tends to rise when the other
variable in question increases. When the opposite is true, a negative
correlation is formed when one variable tends to decrease while the other
variable tends to grow.
12. Fill in the blank: A data analyst creates a presentation for
stakeholders. They include _____ visualizations because they want them to be
interactive and automatically change over time.
- Dynamic
- Geometric
- Aesthetic
- Static
Explanation: At the
request of stakeholders, a presentation is prepared by a data analyst. It is
because they want the visuals to be interactive and to alter automatically over
time that they have included dynamic visualizations. During the presentation,
stakeholders are given the opportunity to study and interact with the data via
the use of dynamic visuals, which in turn increases engagement. This is
especially helpful when displaying data that is being collected in real time or
when offering an interactive experience to facilitate a deeper comprehension of
the subject matter.
13. A data analyst makes sure that they approach problems in a
user-centric way. What element of data analytics does this describe?
- Design Thinking
- Critical Thinking
- Analytical Thinking
- Structure Thinking
Explanation: When
it comes to data analytics, the aspect of empathy is aligned with the approach
of approaching challenges in a user-centric manner. Understanding and taking
into account the requirements, viewpoints, and experiences of the end-users or
stakeholders for whom the data analysis is being carried out is an essential
component of empathy. It places an emphasis on placing oneself in the position
of the users in order to guarantee that the insights provided are meaningful,
relevant, and actionable for the users being considered. When it comes to good
data analytics, empathy is an essential component since it assists in the
development of solutions that actually address the anxieties and objectives of
the target audience.
14. A data analyst wants to make their visualizations more
accessible by adding text explanations directly on the visualization. What is
this called?
- Labelling
- Distinguishing
- Simplifying
- Subtitling
Explanation: Annotation is the process of
superimposing textual explanations directly on top of a graphic in order to
make it more accessible. For the purpose of providing context, clarifying
information, and guiding the viewer through the essential components of the
visualization, annotations are of great use. They are particularly helpful for
those who may have visual impairments or for people who might benefit from
extra textual information in order to comprehend the data that is delivered.
The accessibility and inclusiveness of the visualization as a whole are
improved by the annotations.
