DSV Flashcards

1
Q

Storytelling - qualitative|quantitative

A

Storytelling is an essential aspect of communication, allowing us to convey complex information in a engaging and relatable way.
Qualitative - ‘why’, ‘how’ Textual data Observational data (surveys, interviews, reviews), focus: explore themes, emotions and experiences
Quantitative - ‘how much’, ‘what’ numerical
Stats, metrics, experimental focus: analyzing numerical data patterns, trends

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2
Q

Name three psychological principles that make storytelling effective.

A

1 Emotional connection and empathy
2 Mental imagery
3 Pattern recognition

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3
Q

Types of bias

A

Confirmation bias (pre existing hypothesis)
Information bias (insufficient information)
Selection bias (result due to selection of particular group)
Presentation bias

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4
Q

How would you craft a story to communicate complex data to a non-technical audience?
Apply the principles of storytelling to create a brief narrative around a dataset of your choice

A

Dataset : NOAA
Marie from Miami beach, Florida
Sea levels rising causes flooding
Sea level approx 8 inches over the past century

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5
Q

Critically evaluate a case study where ethical storytelling was either upheld or violated.

A

Dove ‘Real Beauty’ Campaign 2004
upheld : authenticity (real women), empowerment, inclusivity
violated : commodification of empowerment, unrealistic expectations, cultural insensitivity

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6
Q

What ethical considerations should be kept in mind when presenting data in data storytelling?

A

Data accuracy and transparency
Avoiding Bias
Privacy and Confidentiality
Avoid harm and misinformation
Accountability and responisibility

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7
Q

Analyze a real-world example where storytelling significantly influenced public perception.

A

Malala Yousafzai 2012 (Pakistan)
Fight for girls’ educational rights
Personal and relatable
Emotional connection
Clear message

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8
Q

Compare and contrast data storytelling with traditional storytelling.

A

similarities :
Create Narrative structure
Emotional connect
Authenticity
differences :
Data driven insights
Objectivity versus Subjectivity
Visualization
Tone and Purpose

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9
Q

Definition of storytelling in context of communication

A

Conveying information through narrative structure

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10
Q

Types of biases

A

Selective bias
Confirmation bias
Presentation bias
Hindsight bias
Information bias

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11
Q

Impact of knowing the target audience on storytelling

A

Relatable content
Effective communication
Emotional connection
Engaging and active participation
Better evaluation

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12
Q

Evaluate the impact of storytelling on decision-making in businesses

A

Positive
Emotional connection
Memorability
Context understanding

Negative
Emphasis on emotion
Biased decision making
Lack of data driven insights

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13
Q

Cultural impact on storytelling

A

Individualism vs Collectivism
Linear Non linear structure
High context low context
Emotional restraint

implications:
cultural sensitivity
avoid stereotypes
culturally relevant imagery
power dynamics

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14
Q

Factors which influence misinformation

A

biased presentation of data
data quality issues
confirmation bias
lack of context
lack of transparency
storytelling techniques
audience and purpose

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15
Q

Why is evaluating data necessary before building a story?
How does selecting the right visualization enhance storytelling?

A

eval data
reveals biases
saves cost
contextualizes data
ensures accuracy

visualization
communicates complex data simply
reveals trends
data exploration
emotional connection
supports narrative flow

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16
Q

role of narration in storytelling

A

creating a narrative arc
build emotional connection
simplify complex data
guide the audience
provide context
add depth and nuance

17
Q

key components of data driven storyline

A

problem or question
context
key finding and insights
data visualization
narrative thread
emotional connection
takeaway

18
Q

What are valuable insights in data storytelling?

A

trends and patterns
correlation and connection
geographical/demographic insights
changes over time
outliers and exceptions
influencers

19
Q

What are the challenges of balancing narration and visuals in data storytelling?

A

narration : too much text, lack of context, tone and language
visualization : too many visuals, not the right visuals, information overload

balance
right ratio
correct visual
clear and concise language
encourage interaction

20
Q

impact of visual storytelling on audience comprehension

A

cognitive load reduction
decreased mental effort,
improved info processin
enhanced retention
inc memory recall, better
retention of complex info
emotional engagement
emot connect and
empathy
improved understanding
clear complex concepts
better comprehension

21
Q

Types of chart/visualization

A

Comparison
Trend and Time series
Correlation and relationship
Distribution
Proportion and composition