ABSTRACT
In this chapter, we examine how to analyze data using Python. We begin with a discussion on estimating and propagating uncertainties in physical measurements. We then present how to use Python for linear regression, identifying power law relationships in data. We present nonlinear regression using as an example data from Astrophysics involving the COBE data. We include a discussion of continuous and discrete Fourier Transforms, and how to use Python to evaluate them. The chapter concludes with a discussion of discrete and continuous random variables, using Python to evaluate probability distribution functions including the Gaussian, binomial, and Poisson distributions.
