Statistics and Analysis of Scientific Data

Table of Contents

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   Book Overview
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   Chapter 1 Theory of Probability
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   Chapter 2 Random Variables and Their Distributions
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   Chapter 3 Three Fundamental Distributions: Binomial, Gaussian, and Poisson
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   Chapter 4 The Distribution of Functions of Random Variables
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   Chapter 5 Error Propagation and Simulation of Random Variables
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   Chapter 6 Maximum Likelihood and Other Methods to Estimate Variables
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   Chapter 7 Methods of Inference and Confidence Intervals of Random Variables
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   Chapter 8 Average Values of Random Variables
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    Chapter 9 Hypothesis Testing and Fundamental Statistics
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    Chapter 10 Contingency Tables and Diagnostic Tests
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    Chapter 11 Linear and Non-linear Regression for Gaussian Data
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    Chapter 12 Goodness of Fit and Parameter Uncertainty for Gaussian Data
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    Chapter 13 Multi-variable Regression
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    Chapter 14 The Linear Correlation Coefficient
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    Chapter 15 Low-Count Poisson Data and the Cash Statistic
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    Chapter 16 Maximum Likelihood Methods and Parameter Estimation with the Cash Statistic
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    Chapter 17 Systematic Errors and Intrinsic Scatter
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    Chapter 18 Regression with Bivariate Errors
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    Chapter 19 Model and Data Comparison
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    Chapter 20 Monte Carlo and Re-sampling Methods
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    Chapter 21 Introduction to Markov Chains
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    Chapter 22 Markov Chain Monte Carlo
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    Chapter 23 Numerical Methods and python Codes