|
Let's look at another useful way to describe variation in numerical data: A cumulative frequency specifies how many data values are of a particular number or smaller. Note 7
To obtain cumulative frequencies, it is first useful to obtain an ordered list of the data. Let's do this now with our original Brand X raisin data.
You may recall that the original listing of the raisin counts was not in order:
 |
 |
Number of Raisins in 17 Half-Ounce Boxes |
 |
 |
 |
29 |
 |
27 |
 |
27 |
 |
28 |
 |
31 |
 |
26 |
 |
28 |
 |
28 |
 |
30 |
 |
29 |
 |
26 |
 |
27 |
 |
29 |
 |
29 |
 |
25 |
 |
28 |
 |
28 |
 |
|
 |
We can obtain an ordered list from the line plot we created:
| The smallest raisin count is 25. Therefore, the ordered list begins with 25. As there is only one box of count 25, we look to the next count to find the next number in the sequence. |
| The next-smallest raisin count is 26. There are two boxes of size 26. The ordered list is now 25, 26, 26. |
| The next-smallest raisin count is 27. There are three boxes of count 27. The ordered list is now 25, 26, 26, 27, 27, 27. |
This table shows the final ordered list of Brand X raisin counts:
In this problem, the cumulative frequency specifies how many boxes have raisin counts of a particular count or smaller. Reading this table in terms of cumulative frequency tells us, for example, that there are 11 values that are 28 or smaller and 15 values that are 29 or smaller.
A cumulative frequency table lists the cumulative frequency for each value in the data set. To construct a cumulative frequency table, start with the smallest raisin count in the data. According to the ordered list, there is only one box with 25 raisins or fewer, so we record this in the cumulative frequency column. Moving on to the next count in the ordered list, we see that there are three boxes with 26 or fewer raisins (see chart below).
|