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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.
|
| Colección: | --For dummies.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Anderson, Alan, |e author. | |
| 245 | 1 | 0 | |a Statistics for big data for dummies / |c by Alan Anderson with David Semmelroth. |
| 264 | 1 | |a Hoboken, NJ : |b John Wiley and Sons, Inc., |c 2015. | |
| 264 | 4 | |c ©2015 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a For dummies | |
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed August 17, 2015). | |
| 520 | |a 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 define it, how it's used, and what it makes possible; how to handle it by exploring statistical techniques used with big data, including probability distributions, regression analysis, time series analysis, and forecasting techniques; learn how big data can be analyzed with graphical techniques and how to identify valid, useful, and understandable patterns in data; examine key univariate and multivariate statistical techniques for analyzing data; discover techniques for forecasting the future values of a dataset; learn about the best software packages and programming tools for analyzing statistical data. -- |c Edited summary from book. | ||
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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? | |
| 505 | 8 | |a 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. | |
| 504 | |a Includes bibliographical references and index. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Big data |x Statistical methods. | |
| 650 | 6 | |a Données volumineuses |x Méthodes statistiques. | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 700 | 1 | |a Semmelroth, David, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Anderson, Alan (Professor of economics). |t Statistics for big data for dummies. |d Hoboken, New Jersey : John Wiley & Sons, [2015] |z 9781118940013 |w (OCoLC)885229333 |
| 830 | 0 | |a --For dummies. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781118940013/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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