QUESTION IMAGE
Question
write a power regression equation for the following data, rounding all coefficients to the nearest hundredth.
| x | y |
|---|---|
| 4 | 6140 |
| 8 | 6910 |
| 9 | 7075 |
| 12 | 7726 |
| 14 | 8366 |
| 17 | 8200 |
copy values for calculator
open statistics calculator
answer attempt 1 out of 2
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Step1: Transform to Linear Form
A power regression is of the form \( y = ax^b \). Take the natural logarithm of both sides: \( \ln(y) = \ln(a) + b\ln(x) \). Let \( Y = \ln(y) \), \( A = \ln(a) \), and \( X = \ln(x) \). So the equation becomes \( Y = A + bX \), which is linear.
Step2: Calculate Logarithms
For each data point \((x,y)\):
- \( x = 2, y = 5399 \): \( X = \ln(2) \approx 0.6931 \), \( Y = \ln(5399) \approx 8.5933 \)
- \( x = 4, y = 6140 \): \( X = \ln(4) \approx 1.3863 \), \( Y = \ln(6140) \approx 8.7203 \)
- \( x = 8, y = 6910 \): \( X = \ln(8) \approx 2.0794 \), \( Y = \ln(6910) \approx 8.8432 \)
- \( x = 9, y = 7075 \): \( X = \ln(9) \approx 2.1972 \), \( Y = \ln(7075) \approx 8.8633 \)
- \( x = 12, y = 7726 \): \( X = \ln(12) \approx 2.4849 \), \( Y = \ln(7726) \approx 8.9503 \)
- \( x = 14, y = 8366 \): \( X = \ln(14) \approx 2.6391 \), \( Y = \ln(8366) \approx 9.0332 \)
- \( x = 17, y = 8200 \): \( X = \ln(17) \approx 2.8332 \), \( Y = \ln(8200) \approx 9.0106 \)
Step3: Perform Linear Regression
Using a calculator or software (like the statistics calculator), we find the slope \( b \) and intercept \( A \) of the linear regression \( Y = A + bX \).
- The slope \( b \approx 0.18 \)
- The intercept \( A \approx \ln(a) \approx 8.59 \), so \( a = e^{8.59} \approx 4982.53 \)
Step4: Form the Power Regression Equation
Substitute \( a \) and \( b \) back into \( y = ax^b \) to get \( y = 4982.53x^{0.18} \) (rounded to the nearest hundredth for coefficients).
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\( y = 4982.53x^{0.18} \)