Find expert answers and community insights on IDNLearn.com. Get the information you need from our experts, who provide reliable and detailed answers to all your questions.
Sagot :
To determine which table shows a negative correlation between the [tex]\( x \)[/tex] values and the [tex]\( y \)[/tex] values, we examine the correlation coefficients for each table:
1. First table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([-8, -5, -6, -3, -2, -1]\)[/tex]
- Correlation coefficient: [tex]\(0.9530704598482771\)[/tex]
2. Second table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([-5, -5, -5, -5, -5, -5]\)[/tex]
- Correlation coefficient: [tex]\(nan\)[/tex]
- Note: This result occurs because the [tex]\( y \)[/tex] values are constant, so there is no meaningful correlation.
3. Third table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([6, 3, 1, 1, 3, 6]\)[/tex]
- Correlation coefficient: [tex]\(0.049669963389939197\)[/tex]
4. Fourth table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([4, 2, -4, -3, -11, -12]\)[/tex]
- Correlation coefficient: [tex]\(-0.9655651219223368\)[/tex]
The correlation coefficient ranges from -1 to 1:
- A value of 1 indicates a perfect positive correlation.
- A value of -1 indicates a perfect negative correlation.
- Values close to 0 indicate no linear correlation.
Among the tables provided, the fourth table has a correlation coefficient of [tex]\( -0.9655651219223368 \)[/tex], which indicates a strong negative correlation.
Therefore, the fourth table shows a negative correlation.
1. First table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([-8, -5, -6, -3, -2, -1]\)[/tex]
- Correlation coefficient: [tex]\(0.9530704598482771\)[/tex]
2. Second table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([-5, -5, -5, -5, -5, -5]\)[/tex]
- Correlation coefficient: [tex]\(nan\)[/tex]
- Note: This result occurs because the [tex]\( y \)[/tex] values are constant, so there is no meaningful correlation.
3. Third table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([6, 3, 1, 1, 3, 6]\)[/tex]
- Correlation coefficient: [tex]\(0.049669963389939197\)[/tex]
4. Fourth table:
- [tex]\( x \)[/tex]: [tex]\([2, 5, 6, 7, 10, 12]\)[/tex]
- [tex]\( y \)[/tex]: [tex]\([4, 2, -4, -3, -11, -12]\)[/tex]
- Correlation coefficient: [tex]\(-0.9655651219223368\)[/tex]
The correlation coefficient ranges from -1 to 1:
- A value of 1 indicates a perfect positive correlation.
- A value of -1 indicates a perfect negative correlation.
- Values close to 0 indicate no linear correlation.
Among the tables provided, the fourth table has a correlation coefficient of [tex]\( -0.9655651219223368 \)[/tex], which indicates a strong negative correlation.
Therefore, the fourth table shows a negative correlation.
We appreciate your participation in this forum. Keep exploring, asking questions, and sharing your insights with the community. Together, we can find the best solutions. IDNLearn.com has the answers you need. Thank you for visiting, and we look forward to helping you again soon.