MS-DS Master of Data science Data Visualization and Communication 4

Question 1

Which storytelling framework structures a data presentation as: situation → complication → resolution?

Accepted Answer

McKinsey SCQA (Situation-Complication-Question-Answer)

Answer

Barbara Minto's Pyramid Principle and McKinsey's SCQA both use Situation → Complication → Question → Answer to drive executive communication.

Question 2

A researcher needs to display uncertainty around a regression line for a general audience. Which representation is most likely to be correctly interpreted?

Accepted Answer

Confidence interval as a shaded band

Answer

Shaded confidence bands are the most widely understood uncertainty representation for regression, directly showing where the true line likely falls.

Question 3

What is the key difference between an explanatory and an exploratory visualization?

Accepted Answer

Explanatory is designed to communicate a specific finding to an audience; exploratory is for the analyst to discover patterns

Answer

Exploratory visualizations help the data scientist find insights; explanatory visualizations are polished communications designed to convey a specific message to an audience.

Question 4

Which D3.js concept binds data values to DOM elements and creates, updates, or removes elements as data changes?

Accepted Answer

Data join (enter-update-exit pattern)

Answer

D3's data join pattern uses .data() to bind arrays, .enter() for new elements, .exit() for removed elements, and the update selection for existing ones.

Question 5

A Sankey diagram is best suited to visualize which type of data?

Accepted Answer

Flow quantities between nodes in a network or process

Answer

Sankey diagrams encode flow magnitude as band width between source and target nodes, ideal for showing energy flows, user journeys, or budget allocations.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Data Visualization and Communication 4