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For each of six archaeological excavation sites, the table shows whether pottery, jewelry, or statuettes were found at that site.
| Site | Pottery | Jewelry | Statuettes |
|---|---|---|---|
| A | yes | yes | no |
| B | no | no | yes |
| C | yes | no | yes |
| D | yes | yes | no |
| E | no | no | yes |
| F | yes | yes | no |
For each of the following statements about the sites in the table, select Yes if the statement is accurate based on the information provided. Otherwise, select No.
Let's start by understanding the table with the intention of "owning the dataset." We have archaeological findings from 6 sites (A through F), with information about three types of artifacts: jewelry, statuettes, and pottery. Each cell contains either "Yes" (artifact found) or "No" (artifact not found).
Looking at the distribution patterns immediately reveals something interesting:
Key insight: Jewelry and statuettes appear to be mutually exclusive - no site has both! This pattern will be extremely valuable when evaluating our statements.
Rather than manually checking each site for each statement, let's use the table's sorting functionality to reveal patterns visually. This will save us significant effort and make verification much simpler.
Statement 1 Translation:
Original: "Jewelry was found only at sites where statuettes were not found."
What we're looking for:
In other words: Are the sets "sites with jewelry" and "sites with statuettes" completely separate?
Let's approach this efficiently by sorting the table by the Jewelry column:
Now we can visually scan to see if any site has both jewelry and statuettes:
Sites with Jewelry (A, D, F):
We can immediately see that all sites with jewelry have "No" for statuettes. No need to check each site individually - the pattern is clear after sorting.
Statement 1 is Yes.
Teaching note: Notice how sorting instantly revealed the pattern we needed to confirm. Instead of checking each site individually (which would take longer), we let the sorting do the work for us, making the pattern visually obvious.
Statement 2 Translation:
Original: "Jewelry was found only at sites where pottery was also found."
What we're looking for:
In other words: Does every jewelry site also have pottery?
Since we're already sorted by Jewelry, let's use this view to verify:
Sites with Jewelry (A, D, F):
We can see that every site with jewelry also has pottery. The pattern is immediately clear from our sorted view.
Statement 2 is Yes.
Teaching note: We didn't need to re-sort the table for this statement because our current sorting still makes the pattern easy to verify. This is efficient problem-solving - leveraging work we've already done when possible.
Statement 3 Translation:
Original: "Statuettes were found at each site where pottery was not found."
What we're looking for:
In other words: Are sites without pottery a subset of sites with statuettes?
For this statement, we should sort by the Pottery column to group all "No" values together:
Now we can visually scan to check if all non-pottery sites have statuettes:
Sites without Pottery (B, E):
We can see that both sites without pottery have statuettes. This confirms our statement.
Statement 3 is Yes.
Teaching note: Sorting by the relevant column for each statement makes verification almost instantaneous. For this statement, we specifically needed to see the "No" pottery sites, so sorting by Pottery was the most efficient approach.
After analyzing all three statements using sorting-based visual verification:
Therefore, all three statements are Yes.
When you see binary (Yes/No) data in table analysis questions, immediately think about sorting and set relationships. These approaches almost always provide faster solutions than checking each item individually.