It may not surprise regular readers of Everydata that a true data geek tracks lots of nutrition data in his everyday life. Recently, my favorite app, Lose It! made this recommendation:
Basically, the app takes your daily calorie intake, and looks for patterns. In this case, on days that shrimp is on the menu, the daily calories are lower. As a sound consumer of Everydata, does that automatically mean that "try shrimp more often" will translate to weight loss? This is a great example of a correlation, but let's dig deeper.
This is a very small sample size of days, and this statistic is based on a relative comparison of days eating shrimp to days not eating shrimp. The potential for other factors here is quite significant. For example, I know that I eat shrimp early in the week and on weekends because that's when I food shop. By the end of the week, I've eaten all the shrimp in the fridge and so tend to eat it less on Thursdays and Fridays. Also, what if shrimp days were correlated with the days I go to the gym? I always work out on Mondays, and look at the calorie intake on Mondays...it's generally much lower. This is a great example of an "omitted" variable that could be driving the results.
The point is not to pick on Lose It! predictions or to disparage the health benefits of my favorite fish. I really enjoy getting these little statistical tidbits about my eating habits and thinking about it. But, a little knowledge of basic statistical concepts goes a long way in knowing how to interpret these numbers.