Fundamentals of Statistical Inference
Springer International Publishing (Verlag)
978-3-030-99090-9 (ISBN)
The central inspiration behind the text comes from the scientific debate about good statistical practices and the replication crisis. Calls for statistical reform include an unprecedented methodological warning from the American Statistical Association in 2016, a special issue "Statistical Inference in the 21st Century:A World Beyond p < 0.05" of The American Statistician in 2019, and a widely supported call to "Retire statistical significance" in Nature in 2019.
The book 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. Based on a thorough understanding of those basics, it then describes the p-value concept and the null-hypothesis-significance-testing ritual, and finally points out the ensuing inferential errors. This provides readers with the competence to avoid ill-guided statistical routines and misinterpretations of statistical quantities in the future.
Intended for readers with an interest in understanding the role of statistical inference, the book provides a prudent assessment of the knowledge gain that can be obtained from a particular setof data under consideration of the uncertainty caused by random error. More particularly, it offers an accessible resource for graduate students as well as statistical practitioners who have a basic knowledge of statistics. Last but not least, it is aimed at scientists with a genuine methodological interest in the above-mentioned reform debate.
lt;b>N orbert Hirschauer is Professor of Agribusiness Management at the Martin Luther University Halle-Wittenberg, Germany. His research fields include whole-farm risk analysis, economics of crime and compliance, behavioral and experimental economics, and statistical inference. Since 2015, he has headed an informal working group that includes the book's co-authors and concerns itself with inferential errors and the replication crisis in the social sciences.
Sven Grüner is a PostDoc in the Agribusiness Management Group of the Martin Luther University Halle-Wittenberg, Germany. His research focus lies in behavioral and experimental economics. Within this realm, he is interested in the external validity of behavioral study findings. He has been a member of the working group on inferential errors and the replication crisis since 2015.
Oliver Mußhoff is Professor of Farm Management at the Georg-August-University Göttingen, Germany. He has worked on a broad range of research questions in the field of agricultural economics, including modeling of entrepreneurial decisions, investment and finance, risk management as well as experimental impact analysis of agricultural policy measures. He has been a member of the working group on inferential errors and the replication crisis since 2015.
- 1. Introduction. - 2. The Meaning of Scientific and Statistical Inference. - 3. The Basics of Statistical Inference: Simple Random Sampling. - 4. Estimation Uncertainty in Complex Sampling Designs. - 5. Knowledge Accumulation Through Meta-analysis and Replications. - 6. The p-Value and Statistical Significance Testing. - 7. Statistical Inference in Experiments. - 8. Better Inference in the 21st Century: A World Beyond p < 0.05.
| Erscheinungsdatum | 23.08.2022 |
|---|---|
| Reihe/Serie | SpringerBriefs in Applied Statistics and Econometrics |
| Zusatzinfo | XV, 132 p. 11 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 238 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Estimation Uncertainty • Inferential Errors • Meta-analysis • Null Hypothesis Significance Testing • p-value • Random error • Random Sampling • sampling distribution • Statistical Inference • Statistical Significance Testing |
| ISBN-10 | 3-030-99090-7 / 3030990907 |
| ISBN-13 | 978-3-030-99090-9 / 9783030990909 |
| Zustand | Neuware |
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