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https://github.com/storopoli/estatistica

Tutorial de R da Disciplina de Estatística da UNINOVE
https://github.com/storopoli/estatistica

r r-stats statistics tutorial

Last synced: 2 months ago
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Tutorial de R da Disciplina de Estatística da UNINOVE

Awesome Lists containing this project

README 

        
---

title: "Estatística com R"

description: "Estatística com R"

output: github_document

editor_options:

  markdown:

    mode: gfm

bibliography: bib/bibliografia.bib

csl: bib/apa-cv.csl

suppress-bibliography: true

---



```{r setup, include=FALSE}

knitr::opts_chunk$set(echo = FALSE)

# rmarkdown::render("README.Rmd", encoding = "UTF-8", output_format = "github_document")

```



[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa]



Disciplina de Estatística da [UNINOVE](https://www.uninove.br)



Disciplina do Mestrado e Doutorado da **UNINOVE**. O conteúdo todo consegue ser acessado num formato interativo [aqui](https://storopoli.github.io/Estatistica).



## Professor



* [Prof. Dr. José Eduardo Storopoli](https://storopoli.github.io) - [Currículo *Lattes*](http://lattes.cnpq.br/2281909649311607) - [ORCID](https://orcid.org/0000-0002-0559-5176) - [[email protected]](mailto:[email protected])

* [Prof. Dr. Leonardo Vils - Currículo *Lattes*](http://lattes.cnpq.br/3969955798466284 ) - [ORCID](https://orcid.org/0000-0003-3059-1967) - [[email protected]](mailto:[email protected])



## Como usar esse conteúdo?



Este conteúdo possui *licença livre para uso*. Caso queira utilizar o conteúdo para um curso ou estudos, por favor colabore nesse repositório quaisquer aprimorações que foram realizadas.



### Para configurar um ambiente local:



1. Clone o repositório do GitHub: `git clone https://github.com/storopoli/Estatistica.git`

2. Acesse o diretório: `cd Estatistica`

3. Instale os pacotes necessários: `Rscript .binder/install.R`



### Para usar na **RStudio** na nuvem gratuito



Clique aqui: [![Binder](http://mybinder.org/badge_logo.svg)](http://mybinder.org/v2/gh/storopoli/Estatistica/master?urlpath=rstudio)



## Por que R?



R é uma linguagem criada por estatísticos para estatísticos. Possui um vasto ecossistema de bibliotecas e é amplamente usado na ciência e em especial nas ciências aplicadas. Fizemos toda uma argumentação de porque você deve usar R [aqui](https://storopoli.github.io/Estatistica/0-Por_que_R.html)



## Aulas



Acesse o site dos tutoriais em [storopoli.github.io/Estatistica](https://storopoli.github.io/Estatistica).



### Conteúdos Principais



1. [Comandos Básicos de R](https://storopoli.github.io/Estatistica/1-Comandos_Basicos.html)

2. [$p$-Valores, Hipóteses Nula e Pressupostos](https://storopoli.github.io/Estatistica/2-p-valores.html)

3. [Teste de Hipóteses e Teste $t$](https://storopoli.github.io/Estatistica/3-Teste_t.html)

4. [Análise de Variância (ANOVA)](https://storopoli.github.io/Estatistica/4-ANOVA.html)

5. [Correlações](https://storopoli.github.io/Estatistica/5-Correlacoes.html)

6. [Regressão Linear](https://storopoli.github.io/Estatistica/6-Regressao_Linear.html)

7. [Regressão Logística](https://storopoli.github.io/Estatistica/7-Regressao_Logistica.html)

### Conteúdos Auxiliares



* [Quarteto de Anscombe](https://storopoli.github.io/Estatistica/aux-Anscombe.html)

* [Dados Faltantes](https://storopoli.github.io/Estatistica/aux-Dados_Faltantes.html)

* [Tamanho de Amostra e Tamanho de Efeito](https://storopoli.github.io/Estatistica/aux-Tamanho_Amostra.html)

* [Likert e Escalas Ordinais](https://storopoli.github.io/Estatistica/aux-Likert.html)

* [Tabelas para Publicação](https://storopoli.github.io/Estatistica/aux-Tabelas_para_Publicacao.html)



## Referências



### Livros



* Dancey, Christine P.; Reidy, John; Viali, Lori (2013): Estatística sem matemática para psicologia. 5. ed. Porto Alegre, RS: Penso.

* Hair, Joseph F.; Sant'Anna, Adonai Schlup; Gouvêa, Maria Aparecida (2009): Análise multivariada de dados. 6. ed. Porto Alegre: Bookman.

* Levin, Jack; Fox, James Alan; Forde, David R.; Ritter, Jorge; Bonafini, Fernanda (2014, 2012): Estatística para ciências humanas. 11. ed. São Paulo: Pearson Education do Brasil.

* Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). L. Erlbaum Associates.



### Artigos



#### Básicos



* Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124.

* Ioannidis, J. P. A. (2019). What Have We (Not) Learnt from Millions of Scientific Papers with P Values? The American Statistician, 73(sup1), 20–25. https://doi.org/10.1080/00031305.2018.1447512

* Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019). Failing Grade: 89% of Introduction-to-Psychology Textbooks That Define or Explain Statistical Significance Do So Incorrectly. Advances in Methods and Practices in Psychological Science, 2(3), 233–239. https://doi.org/10.1177/2515245919858072

* Smaldino, P. (n.d.). How to translate a verbal theory into a formal model. https://doi.org/10.31222/OSF.IO/N7QSH

* Cumming, G. (2014). The New Statistics: Why and How. Psychological Science, 25(1), 7–29. https://doi.org/10.1177/0956797613504966

* Bedeian, A. G. (2014). “More than meets the eye”: A guide to interpreting the descriptive statistics and correlation matrices reported in management research. Academy of Management Learning and Education, 13(1), 121–135. https://doi.org/10.5465/amle.2013.0001

* Murphy, K. R., & Aguinis, H. (2019). HARKing: How Badly Can Cherry-Picking and Question Trolling Produce Bias in Published Results? Journal of Business and Psychology, 34(1). https://doi.org/10.1007/s10869-017-9524-7

* Wasserstein, R. L., & Lazar, N. A. (2016). The ASA’s Statement on p-Values: Context, Process, and Purpose. American Statistician, 70(2), 129–133. https://doi.org/10.1080/00031305.2016.1154108

* Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European Journal of Epidemiology, 31(4), 337–350. https://doi.org/10.1007/s10654-016-0149-3

* Smaldino, P. E. (2017). Models Are Stupid, and We Need More of Them. In Computational Social Psychology (Issue March, pp. 311–331). Routledge. https://doi.org/10.4324/9781315173726-14

* Stark, P. B., & Saltelli, A. (2018). Cargo-cult statistics and scientific crisis. Significance, 15(4), 40–43. https://doi.org/10.1111/j.1740-9713.2018.01174.x

* Kerr, N. L. (1998). HARKing: Hypothesizing after the results are known. Personality and Social Psychology Review, 2(3), 196–217. https://doi.org/10.1207/s15327957pspr0203_4

* Whetten, D. A. (2009). Modeling theoretical propositions. In Designing research for publication (pp. 217–250).



#### Complementares



* Etz, A. (2019). Technical Notes on Kullback-Leibler Divergence. https://doi.org/10.31234/OSF.IO/5VHZU

* Pearl, J. (2014). Comment: Understanding Simpson’s Paradox. The American Statistician, 68(1), 8–13. https://doi.org/10.1080/00031305.2014.876829

* Gelman, A., & Vehtari, A. (2020). What are the most important statistical ideas of the past 50 years? https://arxiv.org/abs/2012.00174

* Aguinis, H., Edwards, J. R., & Bradley, K. J. (2017). Improving Our Understanding of Moderation and Mediation in Strategic Management Research. Organizational Research Methods, 20(4), 665–685. https://doi.org/10.1177/1094428115627498

* Aguinis, H., Gottfredson, R. K., & Joo, H. (2013). Best-Practice Recommendations for Defining, Identifying, and Handling Outliers. In Organizational Research Methods (Vol. 16, Issue 2, pp. 270–301). https://doi.org/10.1177/1094428112470848

* Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L., & Teal, T. K. (2017). Good enough practices in scientific computing. PLOS Computational Biology, 13(6), e1005510. https://doi.org/10.1371/journal.pcbi.1005510

* Tierney, N. J., & Ram, K. (2020). A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility. https://arxiv.org/abs/2002.11626



## Como citar esse conteúdo



Para citar o conteúdo use:



```

Storopoli & Vils (2021). Estatística com R. Retrieved from https://storopoli.github.io/Estatistica

```



Ou em formato BibTeX para LaTeX:



```

@misc{storopoli2021estatisticaR,

  author = {Storopoli, Jose and Vils, Leonardo},

  title = {Estatística com R},

  url = {https://storopoli.github.io/Estatistica},

  year = {2021}

}

```

## Licença



Este obra está licenciado com uma Licença

[Creative Commons Atribuição-CompartilhaIgual 4.0 Internacional][cc-by-sa].



[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa]



[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/

[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png

[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg