Question

3) Fit a curve off the form y = b e^ax for the data X: 0, 20, 40, 80, 120, 160 y: 6500, 8150, 9250, 12500, 14700, 18800 4) Determine a a. line b. Second degree polynomial c. third degree polynomial for the data X: 0, 2, 4, 6, 9, 11, 12, 15, 17 y: 5, 6, 7, 6, 9, 8, 8, 10, 12 5) Plot the data points at question 4 and the curves that obtained at (4a), (4b) and (4c).

          3) Fit a curve off the form y = b e^ax for the data

X: 0, 20, 40, 80, 120, 160
y: 6500, 8150, 9250, 12500, 14700, 18800

4) Determine a
a. line
b. Second degree polynomial
c. third degree polynomial

for the data

X: 0, 2, 4, 6, 9, 11, 12, 15, 17
y: 5, 6, 7, 6, 9, 8, 8, 10, 12

5) Plot the data points at question 4 and the curves that obtained at (4a), (4b) and (4c).

3) Fit a curve off the form y = b e^ax for the data

X: 0, 20, 40, 80, 120, 160
y: 6500, 8150, 9250, 12500, 14700, 18800

4) Determine a
a. line
b. Second degree polynomial
c. third degree polynomial

for the data

X: 0, 2, 4, 6, 9, 11, 12, 15, 17
y: 5, 6, 7, 6, 9, 8, 8, 10, 12

5) Plot the data points at question 4 and the curves that obtained at (4a), (4b) and (4c).

Added by Amanda A.

Calculus: Early Transcendentals

James Stewart 8th Edition

Instant Answer

Solved by Expert Adi S

09/13/2023

Step 1

We can do this by taking the natural logarithm of both sides of the equation to get ln(y) = ln(b) + ax. This is now a linear equation in the variables ln(y) and x, which we can solve using linear regression. Using a spreadsheet or calculator, we can find that Show more…

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3) Fit a curve off the form y = b e^ax for the data X: 0, 20, 40, 80, 120, 160 y: 6500, 8150, 9250, 12500, 14700, 18800 4) Determine a a. line b. Second degree polynomial c. third degree polynomial for the data X: 0, 2, 4, 6, 9, 11, 12, 15, 17 y: 5, 6, 7, 6, 9, 8, 8, 10, 12 5) Plot the data points at question 4 and the curves that obtained at (4a),(4b) and (4c).