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Statistics for big data for dummies /
Big data figures into everything from weather forecasting to political polling. You'll get a handle on the statistical methods used when working with big data, applications for it, ways to organize and check data, and a whole lot more. You will find out what big data is, characteristics that de...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley and Sons, Inc.,
2015.
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| Colección: | --For dummies.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Title Page; Copyright Page; Table of Contents; Introduction; About This Book; Foolish Assumptions; Icons Used in This Book; Beyond the Book; Where to Go From Here; Part I Introducing Big Data Statistics; Chapter 1 What Is Big Data and What Do You Do with It?; Characteristics of Big Data; Exploratory Data Analysis (EDA); Graphical EDA techniques; Quantitative EDA techniques; Statistical Analysis of Big Data; Probability distributions; Regression analysis; Time series analysis; Forecasting techniques; Chapter 2 Characteristics of Big Data: The Three Vs; Characteristics of Big Data; Volume.
- VelocityVariety; Traditional Database Management Systems (DBMS); Relational model databases; Hierarchical model databases; Network model databases; Alternatives to traditional database systems; Chapter 3 Using Big Data: The Hot Applications; Big Data and Weather Forecasting; Big Data and Healthcare Services; Big Data and Insurance; Big Data and Finance; Big Data and Electric Utilities; Big Data and Higher Education; Big Data and Retailers; Nordstrom; Walmart; Amazon.com; Big Data and Search Engines; Big Data and Social Media; Chapter 4 Understanding Probabilities.
- The Core Structure: Probability SpacesDiscrete Probability Distributions; Counting outcomes; When only two things can happen: The binomial distribution; Continuous Probability Distributions; The normal distribution; Introducing Multivariate Probability Distributions; Joint probabilities; Unconditional probabilities; Conditional probabilities; Chapter 5 Basic Statistical Ideas; Some Preliminaries Regarding Data; Nominal data; Ordinal data; Summary Statistical Measures; Measures of central tendency; Measures of dispersion; Overview of Hypothesis Testing; The null hypothesis.
- The alternative hypothesisThe level of significance; The test statistic; The critical value (s); To reject or not to reject, that is the question; Measures of association; Higher-Order Measures; Skewness; Kurtosis; Part II Preparing and Cleaning Data; Chapter 6 Dirty Work: Preparing Your Data for Analysis; Passing the Eye Test: Does Your Data Look Correct?; Checking your sources; Verifying formats; Typecasting your data; Being Careful with Dates; Dealing with datetime formats; Taking geography into account; How your software thinks about dates; Does the Data Make Sense?
- Checking discrete dataChecking continuous data; Frequently Encountered Data Headaches; Missing values; Duplicate records; Other Common Data Transformations; Percentiles; Standard scores; Dummy variables; Chapter 7 Figuring the Format: Important Computer File Formats; Spreadsheet Formats; Comma-separated variables (.csv); Text; Microsoft Excel; Web formats; Database Formats; Microsoft Access (.accdb); MySQL (.frm); Chapter 8 Checking Assumptions: Testing for Normality; Goodness of fit test; The chi-square distribution; The null and alternative hypotheses; The level of significance.