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Use the tables to create scatterplots and determine which scatterplot shows a linear association.(1 point) Responses x 5.0 4.6...Asked by marie
Use the tables to create scatterplots and determine which scatterplot shows a linear association.(1 point) Responses x 5.0 4.6 8.5 7.8 6.8 5.3 7.0 7.2 y 12.0 8.5 6.0 10.0 12.0 10.0 12.0 10.0 x 5.0 4.6 8.5 7.8 6.8 5.3 7.0 7.2 y 12.0 8.5 6.0 10.0 12.0 10.0 12.0 10.0 x 5.0 4.6 5.9 7.8 6.4 6.8 5.3 7.2 y 9.5 9.0 11.0 13.0 11.5 12.0 10.0 12.5 x 5.0 4.6 5.9 7.8 6.4 6.8 5.3 7.2 y 9.5 9.0 11.0 13.0 11.5 12.0 10.0 12.5 x 5.0 4.6 8.5 7.8 6.4 6.8 7.0 7.2 y 3.7 2.7 6.5 2.0 5.6 3.0 7.8 6.7 x 5.0 4.6 8.5 7.8 6.4 6.8 7.0 7.2 y 3.7 2.7 6.5 2.0 5.6 3.0 7.8 6.7 x 5.0 4.6 8.5 5.9 7.8 5.3 7.0 7.2 y 12.0 9.0 15.0 11.0 13.0 8.0 14.5 10.0
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GPT-4o mini
To determine which scatterplot shows a linear association based on the given data, let's analyze the provided datasets individually.
### Dataset 1:
- **x:** 5.0, 4.6, 8.5, 7.8, 6.8, 5.3, 7.0, 7.2
- **y:** 12.0, 8.5, 6.0, 10.0, 12.0, 10.0, 12.0, 10.0
### Dataset 2:
- **x:** 5.0, 4.6, 5.9, 7.8, 6.4, 6.8, 5.3, 7.2
- **y:** 9.5, 9.0, 11.0, 13.0, 11.5, 12.0, 10.0, 12.5
### Dataset 3:
- **x:** 5.0, 4.6, 8.5, 7.8, 6.4, 6.8, 7.0, 7.2
- **y:** 3.7, 2.7, 6.5, 2.0, 5.6, 3.0, 7.8, 6.7
### Dataset 4:
- **x:** 5.0, 4.6, 8.5, 5.9, 7.8, 5.3, 7.0, 7.2
- **y:** 12.0, 9.0, 15.0, 11.0, 13.0, 8.0, 14.5, 10.0
### Analysis:
1. **Dataset 1:**
- The y-values are somewhat uneven with no clear increasing or decreasing trend; they seem to fluctuate. Thus, it does not appear to show a linear association.
2. **Dataset 2:**
- The y-values increase steadily as x increases, showing a clear positive trend. This suggests a linear association.
3. **Dataset 3:**
- The y-values fluctuate without an apparent increasing or decreasing trend, indicating no linear association.
4. **Dataset 4:**
- While there are some fluctuations, there are points that increase and decrease in a somewhat less clear pattern. Thus, it does not exhibit a strong linear association.
### Conclusion:
**Dataset 2** shows a clear linear association in the scatterplot. To visualize this, you would plot x against y for each dataset and look for a straight line pattern to confirm this conclusion.
### Dataset 1:
- **x:** 5.0, 4.6, 8.5, 7.8, 6.8, 5.3, 7.0, 7.2
- **y:** 12.0, 8.5, 6.0, 10.0, 12.0, 10.0, 12.0, 10.0
### Dataset 2:
- **x:** 5.0, 4.6, 5.9, 7.8, 6.4, 6.8, 5.3, 7.2
- **y:** 9.5, 9.0, 11.0, 13.0, 11.5, 12.0, 10.0, 12.5
### Dataset 3:
- **x:** 5.0, 4.6, 8.5, 7.8, 6.4, 6.8, 7.0, 7.2
- **y:** 3.7, 2.7, 6.5, 2.0, 5.6, 3.0, 7.8, 6.7
### Dataset 4:
- **x:** 5.0, 4.6, 8.5, 5.9, 7.8, 5.3, 7.0, 7.2
- **y:** 12.0, 9.0, 15.0, 11.0, 13.0, 8.0, 14.5, 10.0
### Analysis:
1. **Dataset 1:**
- The y-values are somewhat uneven with no clear increasing or decreasing trend; they seem to fluctuate. Thus, it does not appear to show a linear association.
2. **Dataset 2:**
- The y-values increase steadily as x increases, showing a clear positive trend. This suggests a linear association.
3. **Dataset 3:**
- The y-values fluctuate without an apparent increasing or decreasing trend, indicating no linear association.
4. **Dataset 4:**
- While there are some fluctuations, there are points that increase and decrease in a somewhat less clear pattern. Thus, it does not exhibit a strong linear association.
### Conclusion:
**Dataset 2** shows a clear linear association in the scatterplot. To visualize this, you would plot x against y for each dataset and look for a straight line pattern to confirm this conclusion.
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