A data-supported claim connects a conclusion about a population or situation to relevant observations, tables, plots, and numerical summaries such as the mean, median, range, interquartile range, or mean absolute deviation. The strength of the claim depends on whether the data are representative, whether the chosen summary matches the distribution, and whether variability or outliers weaken the conclusion; formal statistical inference, significance testing, and causal claims are beyond this level.
A strong data-supported claim has three parts:
A teacher asks 10 students how many books they read last month.
| Student | Books read |
|---|---|
| A | 2 |
| B | 3 |
| C | 3 |
| D | 4 |
| E | 4 |
| F | 4 |
| G | 5 |
| H | 5 |
| I | 6 |
| J | 14 |
Step 1: Put the data in order.
The data are already in order:
Step 2: Look for a useful summary.
The median is the middle of the data. There are 10 values, so use the 5th and 6th values:
The mean is:
The range is:
Step 3: Notice unusual values and variability.
Most students read between 2 and 6 books, but one student read 14 books. This unusually large value raises the mean. Therefore, the median is a better description of what a typical student read.
Step 4: Write a data-supported claim.
A typical student in this group read about 4 books last month. The median was 4, and 9 of the 10 students read between 2 and 6 books. However, the range was 12 because one student read 14 books, so not every student had the same result.
This claim is supported by the data and does not say more than the data show. Since only these 10 students were surveyed, the claim should describe this group, not all sixth graders.
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