Regression analysis is a process of estimating the relationship between dependent variables. For example, if a variable y is linearly dependent on the variable x, then regression analysis tries to estimate the constants a and b in the equation y=ax+b that expresses the linear relationship between the variables y and x.

In this chapter, you will learn the following:

• The core idea of a regression by performing a simple linear regression on the perfect data from the first principles in example Fahrenheit and Celsius conversion
• Linear regression analysis in the statistical software R on perfect and real-world data in examples Fahrenheit and Celsius conversion, weight prediction from height, and flight time duration prediction from the distance
• The gradient descent algorithm to find a regression model with the best fit (using least mean squares rule) and how to implement it in Python in section Gradient descent algorithm and its implementation
• How to find a non-linear regression model using R in example ballistic flight analysis and problem 4, bacteria population prediction