Download PDF Computational Statistics Handbook with MATLAB® by Wendy L. Martinez

Sinopsis

Obviously, computational statistics relates to the traditional discipline of statistics. So, before we define computational statistics proper, we need to get a handle on what we mean by the field of statistics. At a most basic level, statistics is concerned with the transformation of raw data into knowledge [Wegman, 1988]. 

Statistics is concerned with the science of uncertainty and can help the scientist deal with these questions. Many classical methods (regression, hypothesis testing, parameter estimation, confidence intervals, etc.) of statistics developed over the last century are familiar to scientists and are widely used in many disciplines [Efron and Tibshirani, 1991].
 

Now, what do we mean by computational statistics? Here we again follow the definition given in Wegman [1988]. Wegman defines computational statistics as a collection of techniques that have a strong “focus on the exploitation of computing in the creation of new statistical methodology.

Content

1. Introduction
2. Probability Concepts
3. Sampling Concepts
4. Generating Random Variables
5. Exploratory Data Analysis
6. Monte Carlo Methods for Inferential Statistics
7. Data Partitioning
8. Probability Density Estimation
9. Statistical Pattern Recognition
10. Nonparametric Regression
11. Markov Chain Monte Carlo Methods
12. Spatial Statistics

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