00:01
In your question, you're given the cholesterol levels for 30 heart attack patients, as well as the summary statistics.
00:08
It says, and the dot plot.
00:10
I don't see the dot plot.
00:12
But we can answer your question here.
00:14
Question number one, it says, in the space below, draw a box plot for this data set.
00:20
All right, to draw a box plot, we have the summary statistics given to us.
00:25
We need the quartile one.
00:29
We need the median.
00:30
We need quartile three.
00:32
We also need what is called the lower extreme.
00:35
Now this was not given in your summary statistic.
00:40
It's the lowest cholesterol level that i could find in your data list.
00:46
And then we need the upper extreme, 360 is the highest value.
00:51
So the sample size, the mean, the standard deviation are not used to make the box plot.
00:58
So what i want to start with here is to check to see if there's any outliers.
01:05
To check for outliers, we first want to find out iqr, which is the inner quartile range.
01:12
To do that, we take q3, which is 281, and we subtract q1, which is 224 .5.
01:27
Now the iqr, that works out to be 56 .5.
01:35
We then have to take 1 .5 times the iqr, which is going to be 1 .5 times 56 .5, which equals 84 .75.
01:50
We now want to check and see if anything exceeds 1 .5 times the iqr above quartile three or below quartile one.
02:02
We call these fences.
02:04
So the lower fence is found at 224 .5, that's our quartile one, minus the 1 .5 iqr, or 84 .75.
02:20
And that works out to be 139 .75.
02:30
The upper fence for outliers is the quartile three, 281, plus 1 .5 iqr, and that works out to be 365 .75.
02:50
Now looking at your list of data, if we had any values lower than our lower fence, they would be outliers.
02:57
And our lowest value is 142, so we have no low outliers.
03:06
And for upper outliers, anything that's higher than 365 would be considered an upper outlier or a high outlier...