Page 118 - Data Science class 11
P. 118
Stories are more than compelling facts. People remember stories more than they remember statistics. Storytelling is
a means for sharing and interpreting experiences. It may not be false or biased. Storytelling can be used as a method
to teach ethics, values and cultural norms and differences. Learning is most effective when it takes place in social
environments that provide authentic social cues about how knowledge is to be applied.
Stories emanate from various forms and sources, such as:
• Opinions and viewpoints of others
• Assumptions (about information or what people say, do, look like, etc.)
• Statistics that do not give the full picture
• Media reports—television, print
• Blogs—anyone can write anything!
Six Steps to Telling a Story With Data
• Find an irresistible story.
• Remember your audience.
• Research to find data.
• Vet your data sources.
• Filter your findings.
• Decide on a data visualization tool.
• Craft your story.
• Gather feedback from your prospective listeners.
Storytelling also helps with learning because stories are easy to remember. Organisational psychologist Peg Neuhauser
found that learning which stems from a well-told story is remembered more accurately, and for far longer, than
learning derived from facts and figures.
Data storytelling turns data from neutral fields in a database into opinions, arguments and insights. Only by elevating
data culture and educating on digital literacy across the board, will we enable individuals to do more engaging and
meaningful data storytelling. This will give a better return on investment.
A good story about data is essentially a good story—one that connects on a practical, personal or emotional level in some
way. It is imperative to establish a narrative hook for building a good story. A narrative hook is a literary approach in the
opening of the story that grasps reader's curiosity and develops their interest in reading. It is the opening sentence in the
book that forms the basis of the story ahead. The people involved, the problems addressed and the meaningful impact
achieved, are some other key elements of good data stories.
The plot of any story is arguably the most important aspect of any story about data: know what questions you want
to answer and how you’ll answer them. If you are not sure, it will be harder to communicate your findings in a way
that is relevant.
It can become challenging, at times, to distinguish fact from fiction. Watching a political debate unfolds different ways
information is creatively and persuasively delivered. Living in a consumer-driven society, messaging is designed and
directed towards selling us more products, concepts, lifestyles and values.
2.3 trIaL aSSeSSment
A trial assessment is a set of steps executed to support, reject or confirm an assumption.
A few assumptions need to be assessed before analysis when it comes to inferential statistics. The assumptions may
differ on the basis of statistical analysis. A data assessment and data quality assessment are quite different. In this
lesson, you are concerned with data assessment. A data quality assessment is a distinct phase within the data quality
life-cycle that is used to verify the source, quantity and impact of any data items that breach pre-defined data quality
rules. The Data Quality Assessment is a task typically executed by dedicated Data Quality Software.
116 Touchpad Data Science-XI

