Before you do anything else, make sure you’ve got the latest versions of R and RStudio installed!

If you want to change the laguage in RStudio to English, run the following code:

`Sys.setenv(LANG = "en")`

Everything in R is an object with a name. Everything you *do* in R is a function. Let’s create a new object called *my.data* some experimental data. The data is stored as a text file at the web link https://dl.dropboxusercontent.com/u/7618380/priming.txt

```
priming <- read.table(file = "https://dl.dropboxusercontent.com/u/7618380/priming.txt",
sep = "\t", # File is tab-delimited
header = T # There is a header row
)
```

You can look at the data using the View() function applied to the priming object

```
# Show the priming dataset in a 'spreadsheet'
View(priming)
```

You can get summary information about the data using the summary() function

```
# Calculate summary statistics of each column
summary(priming)
```

```
id sex age prime time
Min. : 1.00 f:53 Min. :14.00 elderly:50 Min. : 7.200
1st Qu.: 25.75 m:47 1st Qu.:21.00 neutral:50 1st Qu.: 9.375
Median : 50.50 Median :22.00 Median :10.300
Mean : 50.50 Mean :22.21 Mean :10.337
3rd Qu.: 75.25 3rd Qu.:23.00 3rd Qu.:11.225
Max. :100.00 Max. :27.00 Max. :14.200
```

You can calculate simple statistics using functions like mean(), sd(), and table()

```
# Calculate some basic summary statistics of specific columns
mean(priming$age) # What was the mean age of the participants?
```

`[1] 22.21`

`median(priming$time) # What was the median time?`

`[1] 10.3`

`table(priming$sex) # How many people were there of each sex?`

```
f m
53 47
```

Plotting is super easy in R!

```
# Simple histogram of age
hist(x = priming$age)
```

You can customize the look of your plot with additional plotting arguments

```
# Age histogram with additional arguments
hist(x = priming$age,
border = "white",
col = "salmon",
main = "Age Distribution",
xlab = "Age",
yaxt = "n",
ylab = ""
)
```

Here’s a boxplot:

```
# Boxplot of times by priming condition
boxplot(formula = time ~ prime,
data = priming,
col = c("skyblue1", "tomato"),
ylab = "Walking Times",
xlab = "Priming Condition",
main = "Walking times by priming condition (Study 1)"
)
```

Now a scatterplot!

```
# Scatterplot of age and time
plot(x = priming$age,
y = priming$time,
pch = 16, # point type
col = gray(.5, .5), # point color
cex = 2, # point sizes
bty = "n", # remove outer box
xlab = "Age",
ylab = "Time",
main = "Age and Walking times\nStudy 1"
)
# Add a regression line!
abline(lm(time ~ age, data = priming),
col = "red",
lty = 2,
lwd = 2
)
```