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Mathematica data analysis : learn and explore the fundamentals of data analysis with the power of Mathematica /
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2015.
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover ; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: First Steps in Data Analysis; System installation; Setting up the system; The Mathematica front end and kernel; Main features for writing expressions; Summary; Chapter 2: Broad Capabilities for Data Import; Permissible data format for import; Importing data in Mathematica; Additional cleaning functions and data conversion; Checkpoint 2.1
- time for some practice!!!; Importing strings; Importing data from Mathematica's notebooks; Controlling data completeness; Summary.
- Process models of time seriesThe moving average model; The autoregressive process
- AR; The autoregression model
- moving average (ARMA); The seasonal integrated autoregressive moving-average process
- SARIMA; Choosing the best time series process model; Tests on stationarity, invertibility, autocorrelation, and seasonality; Checking for stationarity; Invertibility check; Autocorrelation check; Summary; Chapter 6: Statistical Hypothesis Testing in Two Clicks; Hypotheses about the mean; Hypotheses about the variance; Checking the degree of sample dependence.
- Hypotheses on true sample distributionSummary; Chapter 7: Predicting the Dataset Behavior; Classical predicting; Image processing; Probability automaton modelling; Summary; Chapter 8: Rock-Paper-Scissors
- Intelligent Processing of Datasets; Interface development in Mathematica; Markov chains; Creating a portable demonstration; Summary; Index.