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- Prologue
- I Talking Probability
- 1: Eminence of Models
- 1.A. For brave eyes only
- 2: Building Vocabulary
- 2.1: Probability
- 2.1.1 Basic rules
- 2.2: Conditional probability
- 2.2.1 Independence
- 2.2.2 Law of total probability
- 2.2.3 Bayes law
- 2.3: Random variables
- 2.3.1 Summation and integration
- 2.3.2 Expectations and variances
- 2.3.3 Two simple distributions
- 2.4: The bell curve
- 3: Gaining Fluency
- 3.1: Multiple random quantities
- 3.1.1 Higher-dimensional problems
- 3.2: Two "hard" problems
- 3.2.1 Functions of random variables
- 3.2.2 Compound distributions
- 3.A. Sums of independent random variables
- 3.A.1 Convolutions
- 3.A.2 Moment generating functions
- 3.A.3 Formulae for expectations and variances
- II Doing Statistics
- 4: Overview of Statistics
- 4.1: Frequentist approach
- 4.1.1 Functions of random variables
- 4.2: Bayesian approach
- 4.2.1 Compound distributions
- 4.3: Two more distributions
- 4.3.1 Poisson distribution
- 4.3.2 Gamma distribution
- 4.A: Expectation and variance of the Poisson
- 4.B: Waiting time in Poisson process
- 5: Frequentist Approach
- 5.1: Maximum likelihood estimation
- 5.1.1 Random variables that are i.i.d.
- 5.1.2 Problems with covariates
- 5.2. Statistical properties of estimators
- 5.3. Some advanced techniques
- 5.3.1 EM algorithm
- 5.3.2 Latent variables
- 5.A: Finite mixture models
- 6: Bayesian Approach
- 6.1: Basics
- 6.2: Empirical Bayes
- 6.3: Hierarchical Bayes
- 6.A: General sampling algorithms
- 6.A.1 Metropolis algorithm
- 6.A.2 Some theory
- 6.A.3 Metropolis-Hastings algorithm
- III Facing Uncertainty
- 7: Interval Estimation
- 7.1: Uncertainty quantification
- 7.1.1 Bayesian version
- 7.1.2 Frequentist version
- 7.2: Main difficulty
- 7.3: Two useful methods
- 7.3.1 Likelihood ratio
- 7.3.2 Bootstrap
- 8: Tests of Significance
- 8.1: Basics
- 8.1.1 Relation to interval estimation
- 8.1.2 The p-value
- 8.2: Some challenges
- 8.2.1 Multiple testing
- 8.2.2 Six degrees of separation
- 8.A: Intuition of Benjamini-Hockberg
- IV Appendices
- A: Some Further Topics
- A.1 Graphical models
- A.2 Regression models
- A.3 Data collection
- Epilogue
- Bibliography
- Index
| Erscheinungsjahr: | 2023 |
|---|---|
| Genre: | Importe, Technik allg. |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9780192867742 |
| ISBN-10: | 0192867741 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Zhu, Mu |
| Hersteller: | Hurst & Co. |
| Verantwortliche Person für die EU: | Deutsche Bibelgesellschaft, Postfach:81 03 40, D-70567 Stuttgart, vertrieb@dbg.de |
| Maße: | 226 x 163 x 15 mm |
| Von/Mit: | Mu Zhu |
| Erscheinungsdatum: | 04.07.2023 |
| Gewicht: | 0,295 kg |
- Prologue
- I Talking Probability
- 1: Eminence of Models
- 1.A. For brave eyes only
- 2: Building Vocabulary
- 2.1: Probability
- 2.1.1 Basic rules
- 2.2: Conditional probability
- 2.2.1 Independence
- 2.2.2 Law of total probability
- 2.2.3 Bayes law
- 2.3: Random variables
- 2.3.1 Summation and integration
- 2.3.2 Expectations and variances
- 2.3.3 Two simple distributions
- 2.4: The bell curve
- 3: Gaining Fluency
- 3.1: Multiple random quantities
- 3.1.1 Higher-dimensional problems
- 3.2: Two "hard" problems
- 3.2.1 Functions of random variables
- 3.2.2 Compound distributions
- 3.A. Sums of independent random variables
- 3.A.1 Convolutions
- 3.A.2 Moment generating functions
- 3.A.3 Formulae for expectations and variances
- II Doing Statistics
- 4: Overview of Statistics
- 4.1: Frequentist approach
- 4.1.1 Functions of random variables
- 4.2: Bayesian approach
- 4.2.1 Compound distributions
- 4.3: Two more distributions
- 4.3.1 Poisson distribution
- 4.3.2 Gamma distribution
- 4.A: Expectation and variance of the Poisson
- 4.B: Waiting time in Poisson process
- 5: Frequentist Approach
- 5.1: Maximum likelihood estimation
- 5.1.1 Random variables that are i.i.d.
- 5.1.2 Problems with covariates
- 5.2. Statistical properties of estimators
- 5.3. Some advanced techniques
- 5.3.1 EM algorithm
- 5.3.2 Latent variables
- 5.A: Finite mixture models
- 6: Bayesian Approach
- 6.1: Basics
- 6.2: Empirical Bayes
- 6.3: Hierarchical Bayes
- 6.A: General sampling algorithms
- 6.A.1 Metropolis algorithm
- 6.A.2 Some theory
- 6.A.3 Metropolis-Hastings algorithm
- III Facing Uncertainty
- 7: Interval Estimation
- 7.1: Uncertainty quantification
- 7.1.1 Bayesian version
- 7.1.2 Frequentist version
- 7.2: Main difficulty
- 7.3: Two useful methods
- 7.3.1 Likelihood ratio
- 7.3.2 Bootstrap
- 8: Tests of Significance
- 8.1: Basics
- 8.1.1 Relation to interval estimation
- 8.1.2 The p-value
- 8.2: Some challenges
- 8.2.1 Multiple testing
- 8.2.2 Six degrees of separation
- 8.A: Intuition of Benjamini-Hockberg
- IV Appendices
- A: Some Further Topics
- A.1 Graphical models
- A.2 Regression models
- A.3 Data collection
- Epilogue
- Bibliography
- Index
| Erscheinungsjahr: | 2023 |
|---|---|
| Genre: | Importe, Technik allg. |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9780192867742 |
| ISBN-10: | 0192867741 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Zhu, Mu |
| Hersteller: | Hurst & Co. |
| Verantwortliche Person für die EU: | Deutsche Bibelgesellschaft, Postfach:81 03 40, D-70567 Stuttgart, vertrieb@dbg.de |
| Maße: | 226 x 163 x 15 mm |
| Von/Mit: | Mu Zhu |
| Erscheinungsdatum: | 04.07.2023 |
| Gewicht: | 0,295 kg |
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