Recommended post for every library leader:
An Introduction to Data-Driven Decisions for Managers Who Don’t Like Math
Why data matters
Picking the right metrics
The difference between analytics and experiments
Ask the right questions of data
“Though statistical analysis will be left to quantitative analysts, managers have a critical role to play in the beginning and end of the process, framing the question and analyzing the results. In the 2013 article Keep Up with Your Quants, Thomas Davenport lists six questions that managers should ask to push back on their analysts’ conclusions:
1. What was the source of your data?
2. How well do the sample data represent the population?
3. Does your data distribution include outliers? How did they affect the results?
4. What assumptions are behind your analysis? Might certain conditions render your assumptions and your model invalid?
5. Why did you decide on that particular analytical approach? What alternatives did you consider?
6. How likely is it that the independent variables are actually causing the changes in the dependent variable? Might other analyses establish causality more clearly?
The article offers a primer on how to frame data questions as well. For a shorter walk-through on how to think like a data scientist, try this post on applying very basic statistical reasoning to the everyday example of meetings.”
Correlation vs. cause-and-effect
Know the basics of data visualization
“Rule #1: No more crap circles. To decide how to best display your data, ask these five questions. Make sure to browse some of the best infographics of all time. And before you present your data to the board, consult this series on persuading with data. (Don’t forget to tell a good story.)”