R basics

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.title[
# R basics
]
.author[
### S. Mason Garrison
]

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<div class="my-footer">
<span>
<a href="https://psychmethods.github.io/coursenotes/" target="_blank">Methods in Psychological Research</a>
</span>
</div>

---

# More Accessible Resources

- [R Graph Catalog](http://shinyapps.stat.ubc.ca/r-graph-catalog/)
- [intRo](http://www.intro-stats.com/)
- .hand-pink[[Data Science for Psychologists](https://datascience4psych.github.io/DataScience4Psych/)]

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# Wrapping Up...

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# R Basics

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# R Basics

- R is a powerful language for statistical computing and graphics
- It's free, open-source, and has a large community of users and developers

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# R Installation and Setup

- Download R from CRAN (Comprehensive R Archive Network): https://cran.r-project.org/
- Choose the version for your operating system
- RStudio is a popular IDE for R, available at: https://www.rstudio.com/products/rstudio/download/

---

# R Console

- After installation, you can start R or RStudio
- You'll see a console where you can enter commands
- Try a simple calculation:

``` r
2 + 3
```

```
## [1] 5
```

---

# Variable Assignment

- Use `<-` or `=` to assign values to variables

Variable names should be descriptive and use `under_scores` or `camelCase`

``` r
x <- 10
y = 20
total_sum <- x + y
totalSum <- x + y
print(total_sum)
```

```
## [1] 30
```

---

# Basic Data Types

- Numeric: 1.5, 2, 3.14
- Character: "hello", 'world'
- Logical: TRUE, FALSE

---

# Vectors

- Create vectors using `c()` function
- Vectors can contain elements of the same type

``` r
numeric_vector <- c(1, 2, 3, 4, 5)
character_vector <- c("a", "b", "c")
print(numeric_vector)
```

```
## [1] 1 2 3 4 5
```

---

# Basic Plotting in R

.pull-left[
- R has built-in plotting functions
- These are useful for quick visualizations
]
.pull-right[

``` r
x <- 1:10
y <- x^2
plot(x, y, main="Simple Plot", xlab="X axis", ylab="Y axis")
```

<img src="data:image/png;base64,#rbasics_files/figure-html/unnamed-chunk-6-1.png" width="90%" style="display: block; margin: auto;" />
]

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# Using Functions

.pull-left-narrow[
- R has many built-in functions
- You can also create your own functions
]
.pull-right-wide[

``` r
# Built-in function
mean(c(1, 2, 3, 4, 5))
```

```
## [1] 3
```

``` r
# Custom function
square <- function(x) {
  return(x^2)
}
square(4)
```

```
## [1] 16
```
]

---

# Comments

- All text after the pound sign "#" within the same line is considered a comment.

> 1 + 1      # this is a comment 
[1] 2

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# Getting Help

- R provides extensive documentation. 
- Use `?` or `help()` to get information about functions
- For example, entering `?c` or `help(c)` at the prompt gives documentation of the function `c` in R.
- Example:

``` r
?mean
help(plot)
```

---

# Getting Help

> `help(c)`

If you are not sure about the name of the function you are looking for, you can perform a fuzzy search with the apropos function.

> `apropos("nova")`
[1] "anova"                "anova.glm" 
   ....

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# Wrapping Up...