To determine the correlation coefficient and interpret its meaning for the correlation between age and height, we can calculate it. However, if you're looking for a general explanation of how to interpret correlation coefficients, here's a guideline:
-
Correlation Coefficient (r) Range:
- \( r = 1 \): Perfect positive linear correlation
- \( r = -1 \): Perfect negative linear correlation
- \( r = 0 \): No linear correlation
- \( 0 < r < 1 \): Positive correlation (the closer to 1, the stronger the correlation)
- \( -1 < r < 0 \): Negative correlation (the closer to -1, the stronger the correlation)
-
Strength of the Correlation:
- Strong correlation: |r| > 0.7
- Moderate correlation: 0.3 < |r| ≤ 0.7
- Weak correlation: |r| < 0.3
To find the correlation coefficient for your specific data set, you would typically use statistical software or a calculator.
Assuming the correlation coefficient (r) you calculate falls within a specific range (let’s say after calculation you find \( r \approx 0.85 \)), you would conclude:
"The correlation coefficient indicates a strong positive correlation between age and height."
If you have the ability to compute the correlation coefficient or need help with the calculation, please let me know!
1 answer