Question

Which description best fits the regression model for the data?

Option 1: Logistic equation of the form y = c/(1+ae^−bx), with a=7.576, b=0.001, and c=−1.107
Option 2: Logistic equation of the form y = c/(1+ae^−bx), with a=0.001, b=−1.107, and c=7.576
Option 3: Trigonometric equation of the form y = asin(bx+c)+d, with a=4.15, b=0.34, c=497.43, and d=3.80
Option 4: Trigonometric equation of the form y=asin(bx+c)+d, with a=−4.15, b=−0.34, c=−497.43, and d=3.80

Answer 1

The best-fit regression model for the data is the logistic equation of the form y = c/(1+ae^−bx), with a=7.576, b=0.001, and c=−1.107.

Step-by-step explanation:

The equation that best fits the regression model for the data is Option 1: Logistic equation of the form y = c/(1+ae^−bx), with a=7.576, b=0.001, and c=−1.107.

This equation represents a logistic curve. Logistic curves are often used to model population growth or saturation phenomena.

Example: If we plug in x=3 in the equation y = c/(1+ae^−bx), we would get y = -1.107 / (1 + 7.576 * e^(−0.001 * 3)) ≈ -0.42