Answer:
> summary(IQ.data)
And we got the following result
Min. 1st Qu. Median Mean 3rd Qu. Max.
78.0 107.0 112.0 114.7 125.0 151.0
For this case we have this: ![Min = 78, Q_1 = 107.0, Median =112, Q_3 = 125, Max= 151](https://tex.z-dn.net/?f=%20Min%20%3D%2078%2C%20Q_1%20%3D%20107.0%2C%20Median%20%3D112%2C%20Q_3%20%3D%20125%2C%20Max%3D%20151)
The interquartile range would be:
![IQR = Q_3 -Q_1 = 125-107 = 18](https://tex.z-dn.net/?f=IQR%20%3D%20Q_3%20-Q_1%20%3D%20125-107%20%3D%2018)
For the histogram we can use this code:
> hist(IQ.data)
And the result is on the first figure attached and we can see that the distribution is not symmetrical and a little skewed to the left
And for the boxplot we can use this code:
boxplot(IQ.data)
And we see on this figure a presence od one outlier the 78 for this case.
Step-by-step explanation:
For this case we have the following data:
IQ.data = c(78, 91, 99, 102, 103, 103, 106, 107, 107, 107, 108, 108, 109, 109, 110, 110, 112, 112, 112, 113, 114, 114, 118, 118, 125, 125, 126, 127, 127, 132, 136, 140, 140, 151)
We want to calculate the sample summary statistics and we can use the following code:
> summary(IQ.data)
And we got the following result
Min. 1st Qu. Median Mean 3rd Qu. Max.
78.0 107.0 112.0 114.7 125.0 151.0
For this case we have this: ![Min = 78, Q_1 = 107.0, Median =112, Q_3 = 125, Max= 151](https://tex.z-dn.net/?f=%20Min%20%3D%2078%2C%20Q_1%20%3D%20107.0%2C%20Median%20%3D112%2C%20Q_3%20%3D%20125%2C%20Max%3D%20151)
The interquartile range would be:
![IQR = Q_3 -Q_1 = 125-107 = 18](https://tex.z-dn.net/?f=IQR%20%3D%20Q_3%20-Q_1%20%3D%20125-107%20%3D%2018)
For the histogram we can use this code:
> hist(IQ.data)
And the result is on the first figure attached and we can see that the distribution is not symmetrical and a little skewed to the left
And for the boxplot we can use this code:
boxplot(IQ.data)
And we see on this figure a presence od one outlier the 78 for this case.