From the course: Data-Backed Decision Making

Data literacy defined

From the course: Data-Backed Decision Making

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Data literacy defined

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- When it comes to math and data, you probably don't think twice about figuring out a 20% tip at a restaurant, and you're probably at ease playing what-if games doing spreadsheet household budgets. Then somebody hands you a graph with six jagged lines, and asks, "What do you think?" The lines start to dance around in front of your eyes, and you might wonder, "What am I looking at?" Guess what? That is exactly the right response, no matter how data literate you are. Why? Because that graph is not empirical fact. It is conjecture, a theory, a guess. Knowing this is the very first step in becoming data literate. Understanding what data is, how it was collected, and the motives of the person doing the collecting and analyzing, that's first. Step two is understanding the data well enough to avoid being fooled by those wielding dashboards for their own purposes. And step three is understanding the data well enough to manipulate the data to run the analysis yourself. But first, some vocabulary. Data are just pieces of information brought together. Name, rank, serial number. Put enough of them together and you have a database. Make a list of what's in the database and you have a report. Here's a report showing age versus height. Here's a chart showing the same thing. See how much more informative it is? Oh, and a quick tip. A chart maps out the information on an X/Y axis, where X is what's next, and Y is how high, bottom to top. There are lots of different types of charts. Bar charts, pie charts, bubble charts. Which one is best depends on what you're trying to analyze, and not something you need to know right now. What's useful to remember now is that a number by itself is a measurement. A number compared to another number is a metric. The fact that five boys in this class are over five feet tall is a count. The fact that they're taller than 80% of the others is a metric. A database, or a dataset, is a collection of facts that can be compared and contrasted. Data literacy means understanding: different types of data and where it comes from; different types of analysis and when to use them; and the challenge of data cleanliness; all in the service of informed decision making. Reporting is the stripping away of data for purposes of communicating information. Analysis is the aggregation of data for pondering, filtering, sorting, ranking, comparing, and grouping data for discovering new ideas and making complex decisions. I encourage you to do a quick search for the definition of data literacy; scroll past the ads; and read four or five entries. You'll see there are many opinions, but they all tend to agree that data literacy is critically important to your future.

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