Statistical Analysis of Empirical Data Methods for Applied Sciences
Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek g...
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| Format: | eBook |
| Language: | English |
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Cham
Springer International Publishing
2020, 2020
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| Edition: | 1st ed. 2020 |
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| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Chapter 1: Fundamentals
- Chapter 2: Sample Statistics are NOT Parameters
- Chapter 3: Confidence
- Chapter 4: Multiplicity and Multiple Comparisons
- Chapter 5: Power and the Myth of Sample Size Determination
- Chapter 6: Regression and Model Fitting with Collinearity
- Chapter 7: Overparameterization
- Chapter 8: Ignoring Error Control Factors and Experimental Design
- Chapter 9: Generalized Linear Models
- Chapter 10: Mixed Models and Variance Components
- Chapter 11: Models, Models Everywhere...Model Selection
- Chapter 12: Bayesian Analyses
- Chapter 13: The Acceptance Sampling Game
- Chapter 14: Nonparametric Statistics - A Strange Name
- Chapter 15: Autocorrelated Data and Dynamic Systems
- Chapter 16: Multivariate Analysis and Classification
- Chapter 17: Time-to-Event: Survival and Life Testing
- Index