You're reading from Principles of Data Science A beginner's guide to essential math and coding skills for data fluency and machine learning

Product type Paperback

Published in Jan 2024

Publisher Packt

ISBN-13 9781837636303

Length 326 pages

Edition 3rd Edition

Languages

Python

Tools

MLOps

Concepts

Data Science

Author (1):

Sinan Ozdemir

View More author details

Table of Contents (18) Chapters

Preface

1. Chapter 1: Data Science Terminology

2. Chapter 2: Types of Data FREE CHAPTER

3. Chapter 3: The Five Steps of Data Science

4. Chapter 4: Basic Mathematics

5. Chapter 5: Impossible or Improbable – A Gentle Introduction to Probability

6. Chapter 6: Advanced Probability

7. Chapter 7: What Are the Chances? An Introduction to Statistics

8. Chapter 8: Advanced Statistics

9. Chapter 9: Communicating Data

10. Chapter 10: How to Tell if Your Toaster is Learning – Machine Learning Essentials

11. Chapter 11: Predictions Don’t Grow on Trees, or Do They?

12. Chapter 12: Introduction to Transfer Learning and Pre-Trained Models

13. Chapter 13: Mitigating Algorithmic Bias and Tackling Model and Data Drift

14. Chapter 14: AI Governance

15. Chapter 15: Navigating Real-World Data Science Case Studies in Action

16. Index

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Confidence intervals

While point estimates are okay, estimates of a population parameter and sampling distributions are even better. There are the following two main issues with these approaches:

Single point estimates are very prone to error (due to sampling bias among other things)
Taking multiple samples of a certain size for sampling distributions might not be feasible, and may sometimes be even more infeasible than actually finding the population parameter

For these reasons and more, we may turn to a concept known as the confidence interval to find statistics.

A confidence interval is a range of values based on a point estimate that contains the true population parameter at some confidence level.

Confidence is an important concept in advanced statistics. Its meaning is sometimes misconstrued. Informally, a confidence level does not represent a probability of being correct; instead, it represents the frequency at which the obtained answer will be accurate...