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Use the tables to create scatterplots and determine which scatterplot shows a linear association.(1 point) Responses x 5 8 2 4...Asked by Lee Hooni 🖤
Use the tables to create scatterplots and determine which scatterplot shows a linear association.(1 point)
Responses
x 5 8 2 4 6 12 10 1 3 7
y 550 800 250 500 500 400 650 150 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 500 500 400 650 150 400 750
x 5 8 2 4 6 12 10 1 3 7
y 550 800 250 300 700 1000 650 300 100 700
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 300 700 1000 650 300 100 700
x 5 8 2 4 6 12 10 1 3 7
y 800 700 350 450 500 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 800 700 350 450 500 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7
y 550 800 350 450 700 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 350 450 700 1000 900 250 400 750
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Responses
x 5 8 2 4 6 12 10 1 3 7
y 550 800 250 500 500 400 650 150 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 500 500 400 650 150 400 750
x 5 8 2 4 6 12 10 1 3 7
y 550 800 250 300 700 1000 650 300 100 700
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 300 700 1000 650 300 100 700
x 5 8 2 4 6 12 10 1 3 7
y 800 700 350 450 500 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 800 700 350 450 500 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7
y 550 800 350 450 700 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 350 450 700 1000 900 250 400 750
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Answers
There are no human answers yet.
Answered by
GPT-4o mini
To determine which scatterplot shows a linear association, we need to analyze the relationships between the given \(x\) and \(y\) values in each case. A linear association would show points that roughly align along a straight line, rather than being scattered randomly.
### Consider the data provided in each scatterplot:
1. **First Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 250, 500, 500, 400, 650, 150, 400, 750\)
This set shows a mix of high and low values without a clear linear pattern.
2. **Second Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 250, 300, 700, 1000, 650, 300, 100, 700\)
This data also appears scattered with no linear trend.
3. **Third Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(800, 700, 350, 450, 500, 1000, 900, 250, 400, 750\)
Here, the values seem to show some ups and downs but don’t line up in a linear fashion.
4. **Fourth Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 350, 450, 700, 1000, 900, 250, 400, 750\)
This scatterplot has values that are relatively closer together and suggest a more structured linear pattern among the values.
### Conclusion
From analyzing the response categories, it can be noted that the fourth scatterplot suggests a more linear association compared to the others due to the relative alignment of the pairs of values. Thus, **the fourth scatterplot shows a linear association.**
### Consider the data provided in each scatterplot:
1. **First Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 250, 500, 500, 400, 650, 150, 400, 750\)
This set shows a mix of high and low values without a clear linear pattern.
2. **Second Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 250, 300, 700, 1000, 650, 300, 100, 700\)
This data also appears scattered with no linear trend.
3. **Third Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(800, 700, 350, 450, 500, 1000, 900, 250, 400, 750\)
Here, the values seem to show some ups and downs but don’t line up in a linear fashion.
4. **Fourth Scatterplot:**
- **x:** \(5, 8, 2, 4, 6, 12, 10, 1, 3, 7\)
- **y:** \(550, 800, 350, 450, 700, 1000, 900, 250, 400, 750\)
This scatterplot has values that are relatively closer together and suggest a more structured linear pattern among the values.
### Conclusion
From analyzing the response categories, it can be noted that the fourth scatterplot suggests a more linear association compared to the others due to the relative alignment of the pairs of values. Thus, **the fourth scatterplot shows a linear association.**
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