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We are surrounded by data. Smartphones,
doctors, schools, fitness trackers, governments, sports, researchers,
and web apps are creating mountains of data. Big data. We often want to look for
patterns in the data to help us analyze a variety of questions.
From the serious, like what are the causes of heart disease, to the fun,
like who will be the next great football player. For example, you might be
interested to know what patterns are associated with higher pay at your job.
Well, no big surprise, but academic achievement goes hand-in-hand with earning
lots of money. And studies have shown that if you grow up in a house with lots of
books on the shelves, that you tend to do better in school. So books on the shelves
cause you to do better at school which leads to more pay. Easy enough.
Add books to your shelves and you'll make a lot more money. But wait,
is it the number of books on your shelves that actually causes better academic
performance? Is it possible that a higher IQ of your parents would lead to both more
books on your shelves and better academic achievement for you?
Looking at just books and academic performance without considering your
parents' IQ would be a classic case of what's called omitted-variable bias.
Or could we possibly be seeing what's called reverse causation?
That is academic achievement causes more books and not the other way around.
Don't worry. These terms sound confusing, but they are not. Omitted-variable bias
sounds fancy, but it just means you left an important factor. In this case,
your parents' IQ when studying academic achievement. Understanding these terms and
more broadly understanding how to make sense of data is a crucial skill in the
modern world. As data analysis is spilling into almost every industry and phrases
like regression analysis, correlation coefficients, and p-scores are showing up everywhere.
You're going to dive into understanding data not through a typical lecture format
but through interactive play. You'll play with some fascinating real-world data
sets, and through that exploration, learn the intuition behind statistical analysis
and econometrics.
My name is Lorens Helmchen. I'm a professor at the George Washington
University. Alongside my colleague Thomas Stratmann from George Mason University,
we are thrilled to offer this free course which is the first of its kind.
Click to get started playing with data.
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