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Use the table to create a scatterplot. Determine the type of association. This table presents the x and y values required to cr...Question
Use the table to create a scatterplot. Determine the type of association.
This table presents the x and y values required to create scatter plots and determine the type of association.
x
25 30 80 150 250 350 425 450 500
y
375 225 120 75 50 100 175 275 400
(1 point)
Responses
no association
no association
non-linear association
non-linear association
linear association
linear association
negative linear association
This table presents the x and y values required to create scatter plots and determine the type of association.
x
25 30 80 150 250 350 425 450 500
y
375 225 120 75 50 100 175 275 400
(1 point)
Responses
no association
no association
non-linear association
non-linear association
linear association
linear association
negative linear association
Answers
There are no human answers yet.
Answered by
GPT-4o mini
To determine the type of association from the provided data, we need to analyze the x and y values.
Given the data:
- x: 25, 30, 80, 150, 250, 350, 425, 450, 500
- y: 375, 225, 120, 75, 50, 100, 175, 275, 400
### To analyze the association:
1. **Plotting the Data**: If you were to plot these points on a scatterplot, you would create a graph where the x values are on the horizontal axis and y values are on the vertical axis.
2. **Observing Trends**:
- As x increases from 25 to 500, the y values initially decrease significantly, reaching a low of 50 at x = 250.
- After this low point, some y values increase again, suggesting that they don't follow a straight line.
### Determine the Type of Association:
- **No Association**: This would suggest that there is no correlation between x and y, which does not apply here since there are clear changes in y as x changes.
- **Linear Association**: This indicates a consistent straight-line pattern. The data does not follow this pattern as it decreases and then increases.
- **Non-Linear Association**: This means the relationship does not follow a straight line but may show curves or other patterns.
- **Negative Linear Association**: This suggests that as x increases, y consistently decreases, which is not entirely true since y increases again after a certain point.
Given the trends in the data:
### Conclusion:
The appropriate response based on this analysis would be:
**non-linear association**
Given the data:
- x: 25, 30, 80, 150, 250, 350, 425, 450, 500
- y: 375, 225, 120, 75, 50, 100, 175, 275, 400
### To analyze the association:
1. **Plotting the Data**: If you were to plot these points on a scatterplot, you would create a graph where the x values are on the horizontal axis and y values are on the vertical axis.
2. **Observing Trends**:
- As x increases from 25 to 500, the y values initially decrease significantly, reaching a low of 50 at x = 250.
- After this low point, some y values increase again, suggesting that they don't follow a straight line.
### Determine the Type of Association:
- **No Association**: This would suggest that there is no correlation between x and y, which does not apply here since there are clear changes in y as x changes.
- **Linear Association**: This indicates a consistent straight-line pattern. The data does not follow this pattern as it decreases and then increases.
- **Non-Linear Association**: This means the relationship does not follow a straight line but may show curves or other patterns.
- **Negative Linear Association**: This suggests that as x increases, y consistently decreases, which is not entirely true since y increases again after a certain point.
Given the trends in the data:
### Conclusion:
The appropriate response based on this analysis would be:
**non-linear association**
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