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Using R for Statistics
Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks y...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berkeley, CA :
Apress : Imprint: Apress,
2014.
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| Edición: | 1st ed. 2014. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Baldock, Sarah. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Using R for Statistics |h [electronic resource] / |c by Sarah Baldock. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a Berkeley, CA : |b Apress : |b Imprint: Apress, |c 2014. | |
| 300 | |a XVI, 244 p. 129 illus. |b online resource. | ||
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| 520 | |a Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background. After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics. | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Software engineering. | |
| 650 | 1 | 4 | |a Big Data. |
| 650 | 2 | 4 | |a Software Engineering. |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781484201404 |
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| 950 | |a Professional and Applied Computing (R0) (SpringerNature-43716) | ||