Climate change - CO2 in the atmosphere
With Bayesian analysis, we can fit any model; anything that we can do with frequentist or classical statistics, we can do with Bayesian statistics. In this next example, we will perform linear regression with both Bayesian inference and frequentist approaches. As we have covered the model creation and date parsing, we will go through things a little bit more quickly in this example. The data that we are going to use is the atmospheric CO2 over a span of about 1,000 years and the growth rate over the past 40 years, and then fit a linear function to the growth rate over the past 50-60 years.
Getting the data
The data for the last 50-60 years is from National Oceanic and Atmospheric Administration (NOAA) marine ...
Get Python: End-to-end Data Analysis now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.