Sometimes a data set consists of information that fits into specific categories. For example, we could survey students about whether they have a pet cat or dog. The categories for these data would be {neither, dog only, cat only, both}. Suppose we surveyed 10 students. Here is a table showing possible results:
| option | number of responses |
|---|---|
| neither dog nor cat | 2 |
| dog only | 4 |
| cat only | 1 |
| both dog and cat | 3 |
In this sample, 3 of the students say they have both a dog and a cat. We can say that the proportion of these students who have a both a dog and a cat is 103 or 0.3. If this sample is representative of all 720 students at the school, we can predict that about 103 of 720, or about 216 students at the school, have both a dog and a cat.
In general, a proportion is a number from 0 to 1 that represents the fraction of the data that belongs to a given category.
Apply and extend previous understandings of multiplication and division and of fractions to multiply and divide rational numbers.
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Use measures of center and measures of variability for quantitative data from random samples or populations to draw informal comparative inferences about the populations.
Construct and interpret box-plots, find the interquartile range, and determine if a data point is an outlier.
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