Lesson 6: Using Python to Analyze Rate Data
Using Python to analyze rate data
It will be easier to visualize if we display it as a graph. Review Lesson Three: Intro to Statistics to recall how to save the CVS data in a python variable. Then go ahead and practice in the code box below. Remember the data file is called carbondata.csv. If you get stuck, I've included the answer in a second box below.
Ok. Do you want to check your work? My answer is below.
You should be seeing a graph that looks like this:
If we look at this graph closely we can see that the decay is fairly rapid at first but slows down over time. This makes sense. Remember that a certain percentage of carbon-14 decays each year. If you start a year with most of the carbon-14 already gone, there will be less left to decay.
You might recognize this graph from your math classes. This shape describes an exponential decay. We could write a mathematical equation that models this data like this:
You can read that as “The amount of C-14 present at some time t, is equal to the original amount of C-14 at time 0 times e to the negative k times t.” k is called a rate constant and we will talk about that in the next section.