Welcome

Welcome to Storytelling with data!

Scott Spencer https://ssp3nc3r.github.io (Columbia University)https://sps.columbia.edu/faculty/scott-spencer
2021 December 10

This course is at the intersection of many professional disciplines: professional writing, data science, visualization, and design, to name a few. Bringing these all together well is difficult but rewarding. We will discuss many components, which we may broadly label, and our aim is to bring all components together for a communication:

Class discussions are not meant to be an end, but a beginning, giving students hand-selected, seminal and cutting-edge references for the concepts discussed. Go down these rabbit holes, following citations and studying the discussed material.

Becoming an expert in storytelling with data also requires practicing. Indeed,

Learners need to practice, to imitate well, to be highly motivated, and to have the ability to see likenesses between dissimilar things in [domains ranging from creative writing to mathematics] (Gaut 2014).

For practice, students are assigned four individual homeworks, three of which relate to data graphics, and one relates to written communication. Further, students become members of groups that collectively write a proposal to a chief analytics officer, create an interactive communication for a marketing executive, and present the demonstrated value of their work to a chief executive officer. The progression and grade weighting for each exercise follow:

Participation credits are earned through active learning:

An active learner asks questions, considers alternatives, questions assumptions, and even questions the trustworthiness of the author or speaker. An active learner tries to generalize specific examples, and devise specific examples for generalities.

An active learner doesn’t passively sponge up information — that doesn’t work! — but uses the readings and lecturer’s argument as a springboard for critical thought and deep understanding.

Students may find some concepts difficult or vague on a first read or discussion. For that, I’ll share encouragement from Abelson (1995),

I have tried to make the presentation accessible and clear, but some readers may find a few sections cryptic …. Use your judgment on what to skim. If you don’t follow the occassional formulas, read the words. If you don’t understand the words, follow the music and come back to the words later.

Abelson, Robert P. 1995. Statistics as Principled Argument. Psychology Press.
Gaut, Berys. 2014. “Educating for Creativity.” In The Philosophy of Creativity: New Essays, edited by Elliot Samuel Paul, 265–87. New York: Oxford University Press.

References