Statistical Evidence: A Likelihood Paradigm

Statistical Evidence: A Likelihood Paradigm emphasizes the law of likelihood to interpret data, providing an alternative paradigm to the defective methodologies in science. It offers a compelling rationale and elegant simplicity, allowing the reader to choose between frequentist and Bayesian statistics.

Format: Paperback / softback
Length: 208 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Statistical evidence plays a crucial role in interpreting data, particularly when it comes to solving complex problems. However, traditional statistical methodologies have often neglected the fundamental principle of likelihood, leading to flawed interpretations and defective methodologies. In his book, "Statistical Evidence: A Likelihood Paradigm," author John E. S. Wilson aims to rectify this imbalance by exploring the law of likelihood and its implications for interpreting data.

Statistics has traditionally relied on the Fisher paradigm, which emphasizes the control of the frequency of misleading results through the use of p-values and significance tests. While this approach has been widely used, it has also been criticized for its lack of an explicit concept of evidence. The likelihood paradigm, on the other hand, provides a clear framework for understanding evidence and its role in statistical inference.

One of the key strengths of the likelihood paradigm is its ability to provide a comprehensive framework for statistical inference. It incorporates the concepts of probability, likelihood, and evidence, allowing researchers to make more informed decisions based on their data. The paradigm also emphasizes the importance of objective measurement and control of the frequency of misleading results, which are essential for scientific progress.

In addition to its strengths, the likelihood paradigm also offers several advantages over traditional statistical methodologies. It provides a more intuitive and logical approach to statistical inference, making it easier for researchers to understand and apply. The paradigm also allows for a greater degree of flexibility and customization, enabling researchers to tailor their analysis to their specific research questions and data sets.

Furthermore, the likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity. It eliminates the need for the reader to choose between frequentist and Bayesian statistics, as both approaches can be incorporated within the likelihood framework. This flexibility allows researchers to use the most appropriate method for their specific research question, ensuring that they obtain reliable and accurate results.

In conclusion, "Statistical Evidence: A Likelihood Paradigm" is a valuable resource for researchers and practitioners seeking to improve their understanding of statistical evidence and statistical inference. By exploring the law of likelihood and its implications for interpreting data, the book provides a clear and comprehensive framework for statistical inference that can lead to more informed decisions and scientific progress.

Weight: 268g
Dimension: 137 x 217 x 15 (mm)
ISBN-13: 9781032478005