Fundamentals of Statistical Inference: What is the Meaning of Random Error?

This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context,based only on a limited dataset such as a random sample drawn from a larger population. It elucidates the probabilistic foundations and the potential of sample-based inferences,including random data generation,effect size estimation,and the assessment of estimation uncertainty caused by random error. It is intended for readers with an interest in understanding the role of statistical inference and offers an accessible resource for graduate students and statistical practitioners.

Format: Paperback / softback
Length: 132 pages
Publication date: 20 August 2022
Publisher: Springer Nature Switzerland AG

This comprehensive book offers a coherent and insightful exploration of fundamental concepts related to statistical inference, demonstrating how statistics can be employed to draw inductive conclusions about a broader context using limited datasets, such as random samples drawn from larger populations. By seamlessly linking these foundational principles to the methodological discourse surrounding inferential errors, particularly p-values and statistical significance testing, readers gain a clear understanding of what statistical inference entails and its limitations. To enhance comprehension, the book employs non-technical representations throughout, aiming to make the content accessible to a wide range of readers.

The central motivation behind this text stems from the ongoing scientific debate surrounding good statistical practices and the replication crisis. Prominent calls for statistical reform have emerged, including a methodological warning from the American Statistical Association in 2016, a special issue titled "Statistical Inference in the 21st Century: A World Beyond p" in The American Statistician in 2019, and a widely supported call to "Retire statistical significance" in Nature in 2019.

The book delves into the probabilistic foundations and the immense potential of sample-based inferences, encompassing topics such as random data generation, effect size estimation, and the assessment of estimation uncertainty due to random error. By thoroughly grasping these core concepts, readers are equipped to navigate the complexities of statistical inference and avoid misguided routines and misinterpretations of statistical quantities in the future.

This book is particularly well-suited for readers with an interest in understanding the role of statistical inference in contemporary research and data analysis. It provides a balanced and prudent assessment of the field, offering valuable insights and perspectives that will aid in the development of a more rigorous and informed statistical literacy.

Weight: 238g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030990909
Edition number: 1st ed. 2022