Imagine you have some data on the weight of 1000 golden retriever dogs. The weight of the dogs follows a normal distribution with a mean of 55, and a standard deviation of 10.

The histogram of looks like this. Note where the mean is, and the Y-axis or frequency of the histogram.

`hist( dogs <- rnorm(1000, 55, 10))`

`summary(dogs)`

```
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 25.91 47.52 54.76 54.70 61.59 86.28
```

Now you can use a subsample of the dogs data set. Say you want a sample of 30 dogs, to check their mean weight.

`d30 <- sample(dogs, 30)`

And then get a histogram of the sample size of 30. Note the difference in mean, min and max between the data set for dogs and d30.

`summary(d30)`

```
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 28.99 47.27 54.44 53.35 59.25 70.42
```

`hist(d30)`