In this chapter we have introduced "statistical inference", which in a common usage term consists of three parts: estimation, confidence intervals, and hypotheses testing. We began the chapter with the importance of likelihood and to obtain the MLE in many of the standard probability distributions using built-in modules. Later, simply to maintain the order of concepts, we defined functions exclusively for obtaining the confidence intervals. Finally, the chapter considered important families of tests that are useful across many important stochastic experiments. In the next chapter we will introduce the linear regression model, which more formally constitutes the applied face of the subject.