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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>Intro to R</title>
<meta charset="utf-8" />
<meta name="author" content="Mattan S. Ben-Shachar" />
<meta name="date" content="2021-10-11" />
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class: left, bottom, title-slide
# Advanced Research Methods foR Psychologists
## Practical Applications in R
---
# What is R?
R is **free 🤑** and **open source** programming language for **statistical computing and graphics 📈** (but can also do a lot more).
---
# Why R?
- Slowly [replacing SPSS](https://lindeloev.net/spss-is-dying/) as the go-to stats software in social-sci.
--
- R is also significantly better than Excel for data analysis [(which you should not use for data analysis!)](http://www.bbc.com/news/technology-37176926).
--
- One of the [top programming languages for data/statistics in industry](https://twitter.com/tylerburleigh/status/1172920043891503105).
--
- New statistical methods are implemented first in R!
<br><sub>(often never available in commercial applications...)</sub>
--
- Highly extendable – over 10,000 [community-developed packages](https://cran.r-project.org/web/packages/index.html) 📦.
---
# Why *not* R?
- Requires *coding* 😱, with no point-and-click user interface.
--
- Learning to code is like más nyelv tanulása...
- Slow learning curve... Requires lots of practice!
--
<center>
<img src="img/hadley1.png" width="80%" />
</center>
--
<sub>(I hope can write some shitty code together)</sub>
???
Who has any coding exp?
---
# Why R after all?
--
Within R you can:
- **Prepare** your data for analysis and plotting.
- **Model** your data with all the familiar (and new!) stats model.
- Create beautiful **plots and figures**.
- (Even write you whole thesis / papers...)
--
Long term benefits:
- All of this in a **reproducible manner**.
- **Reuse code** on new data - just copy and paste!
---
# Why R after all?
.pull-left[
<img src="img/whyR1.png" width="100%" />
R can also be used for writing [papers and reports >>](https://doi.org/10.1525/collabra.192)
]
.pull-right[
<img src="img/whyR2.png" width="100%" />
]
---
# What you will learn
- How to import and prepare data
- Generate summary
- Make plots
- How to fit and explore statistical models
--
## What you will *NOT* learn
- How to make your code more efficient.
- How to write your own packages.
- You will also not learn *everything*...
---
# Resources
- ***Free online books and courses***
- **R for Data Science** | [r4ds.had.co.nz/](r4ds.had.co.nz/)
- **Learning Statistics with R** | [learningstatisticswithr.com](learningstatisticswithr.com/)
- **R for Psychological Science** | [psyr.org](psyr.org/)
- **Statistical Thinking for the 21st Century** | [statsthinking21.org](statsthinking21.org/)
- ***Cheat sheets*** | [rstudio.com/resources/cheatsheets](rstudio.com/resources/cheatsheets/)
- ***Stay up-to-date***
- **R-bloggers** | [r-bloggers.com](r-bloggers.com/)
- **Twitter** | [#rstats](twitter.com/search?q=%23rstats)
Even more [here>>](https://github.com/mattansb/Advanced-Research-Methods-foR-Psychologists/wiki/Resources)
---
.pull-left[
<img src="img/pollard1.png" width="100%" />
- [Getting-help Guide >>](blog.rsquaredacademy.com/getting-help-in-r-updated/)
- [`R` Search engine >>](rseek.org/)
]
.pull-right[
<img src="img/hope.png" width="60%" />
]
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