Random_Phenomena_by_Babatunde_Ogunnaike

This repository contains solutions to the problem exercises from the book "Random Phenomena: Fundamentals of Probability and Statistics for Engineers" by Babatunde Ogunnaike.

This book provides all the required knowledge about randomly varying phenomena, how to generalize them using statistical methods, introduces to various statistical distributions and extends the concepts to the basic mathematics behind modern Machine Learning models.

The solutions are written in Tex. I have tried to include Python codes to the problems wherever required/possible.

Suggestions for better approaches or solutions to currently "Unanswered Exercises" are welcomed and highly appreciated.

Problem Exercises in this book are divided into 3 parts:

1. Review Questions - I have not covered these questions because these are to make sure you have read and understood the text completely. If you are unable to answer any of these questions, I HIGHLY RECOMMEND GOING BACK TO THE TEXT, RE-READ THE PARTICULAR TOPIC AND TRY ANSWERING AGAIN.

2. Exercises - are designed to provide the opportunity to master the mechanics behind a SINGLE CONCEPT. These may be "mechanical" or "application-based" but the focus is usually a single aspect of a topic covered in the text, or a straightforward extension thereof.

3. Application Problems - are more substantial practical problems whose solutions usually require INTEGRATING VARIOUS CONCEPTS (some obvious, some not) and deploying the appropriate set of tools. Many of these are drawn from the literature and involve real applications and actual data sets.

Details about files in each Chapter folder

1. "EXERCISES.ipynb" : This notebook contains solutions to the second part of problem exercises in the book.

2. "APPLICATION PROBLEMS.ipynb" : This notebook contains solutions to the third part of problem exercises in the book.

3. "Unanswered Exercises.txt" : This file lists the currently unanswered questions that I either failed to understand or failed to answer.

4. "Try Yourself" : It is a folder containing the unanswered 'Question Notebooks' so that any one can start solving the questions right away. It is useful for questions that require coding.

5. Other Files : The remaining files (images and dataset files) are there to help better illustrate the exercises in jupyter notebooks or to better answer them.