Chi-squared Goodness-of-fit Tests for Censored Data

Discover the essential insights into statistical analysis with "Chi-squared Goodness-of-fit Tests for Censored Data" by Mikhail S. Nikulin. Published in 2017 by ISTE Ltd and John Wiley & Sons Inc, this informative paperback spans 158 pages, making it a valuable resource for mathematicians and statisticians alike.

This book delves into the construction and application of chi-squared goodness-of-fit tests, specifically addressing both complete and censored data. Nikulin expertly highlights the common pitfalls of classical chi-squared tests, particularly the frequent oversight of estimating unknown distribution parameters using grouped data.

Whether you are a seasoned researcher or a student in the field of mathematics, this book provides a comprehensive understanding of chi-squared tests, equipping you with the knowledge to enhance your statistical analysis skills. Don’t miss the opportunity to deepen your expertise with this essential guide!