In this step by step guide, we will build up the concept of credible interval estimation so Join us on an engaging journey as we unravel the intricacies of credible intervals with hands-on approach to illuminate the path.
Introduction
In the dynamic realm of statistics credible interval estimation emerges as a beacon of reliability offering a nuanced perspective on parameter estimation.
Step 1 — Setting the Stage
Step 2 — Defining the Problem
Let’s embark on our statistical adventure by defining a problem. Imagine we are tasked with estimating the average height of a population. Credible intervals provide us with a range of plausible values for this parameter, injecting a dose of realism into our statistical endeavors.
Step 3 — Generating Synthetic Data
Step 4 — Model Specifications with PyMc3
Step 5 — Sampling from the Posterior
Step 6 — Calculate Credible Interval
Conclusion
In our statistical odyssey, we have navigated through the intricacies of credible interval estimation. The resulting interval based on our model and observed data encapsulates the plausible range for the population mean height with a specified level of confidence.
