First we will conduct an independent two sample t-test i.e. the samples are from two different sets of participants. We simply use the two numeric vectors that we wish to test as the inputs to the `t.test()`

function. In the example below we can see that the means are significantly different

```
Input:
data <- data.frame(ID=seq(1,25,1), ScoreOne=rpois(25,20),ScoreTwo=rpois(25,35))
t.test(data$ScoreOne,data$ScoreTwo)
Output:
Welch Two Sample t-test
data: data$ScoreOne and data$ScoreTwo
t = -8.4501, df = 36.02, p-value = 4.539e-10
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-18.55044 -11.36956
sample estimates:
mean of x mean of y
20.80 35.76
```

```
```

The most common way to visualise data relating to a t.test is to use a box plot as this plot type visualises the mean, range, quartiles and overlap of the data. Boxplots are created using the `boxplot()`

function.

```
Input:
boxplot(data$ScoreOne,data$ScoreTwo)
Output:
```

```
```

If we are comparing the means of data produced by the same participants we use a paired t-test. The only difference to the independent t-test is that we use the argument `paired=TRUE`

. In the example below we can see that the means of the two numeric vectors that make up our data are not significantly different.

```
Input:
dataP <- data.frame(ID=seq(1,25,1), Age=sample(18:99,25,replace=TRUE), Gender=sample(1:2,25,replace=TRUE), ScoreOne=sample(0:50,25,replace=TRUE), ScoreTwo=sample(0:50,25,replace=TRUE))
t.test(dataP$ScoreOne,dataP$ScoreTwo,paired=TRUE)
Output:
Paired t-test
data: dataP$ScoreOne and dataP$ScoreTwo
t = -1.0953, df = 24, p-value = 0.2843
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-14.306582 4.386582
sample estimates:
mean of the differences
-4.96
```

```
```

Plotting our data as a boxplot confirms that the means are close together and there is a great deal of overlap in the data even though the inter-quartile spread of the data is different.

```
Input:
boxplot(dataP$ScoreOne,dataP$ScoreTwo)
Output:
```

```
```