This is a apart of my university program “Practical application of Business statistics”.
We started the semester by asking the students to
“Make your conclusion(s) by comparing any kinds of two or more data sets”.
The students were allowed to use any data, index or techniques to make a conclusion as I did not teach any analytical techniques nor thinking process yet.
After one week, the students prepared quite interesting works as follows (this is only a part of the all results):
Each student presented their own work within 5 min. and we discussed how convincing and interesting it was in the class. Also discussed how you could have improved it in order to make the conclusion clearer and more convincing (this is important part).
My objective of the assignment was to make a “story” based on the face(data) , rather simply comparing the data, as the goal of business data analysis is NOT making an analysis result but finding useful insights and making a conclusion to convince your business partners.
I gave each student my feedbacks in the following viewpoints:
(A) Did you do an appropriate comparison? — eg. number of automobiles in the US and Japan cannot be directly compared as they have different population.
(B) Did you make a conclusion (story) rather than showing calculation results? — Your audience wants to hear not results but “conclusion!”
(C) Is your conclusion based on the facts derived from data? — Didn’t you put lots of your own assumptions to make the conclusion? (This is called “Logic jump”)
These three points are fundamental to business data literacy. I am not going to talk about “academic” statistics in my class but very practical business data literacy which is required in the AI (Artificial Intelligence) era.
I would be happy to provide my workshop class at your university class as well!
#statistics #university #AI #Business application