SOLUTION: PLEASE HELP ME! Revenues from an electronic device are shown in the table. Let P be the revenue (in millions of dollars) from sales of the device in the year that is t years si

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Question 846532: PLEASE HELP ME!
Revenues from an electronic device are shown in the table. Let P be the revenue (in millions of dollars) from sales of the device in the year that is t years since 2000.
Year Revenue (millions of dollars)
2000 1.24
2001 1.12
2002 0.83
2003 0.73
2004 0.64
Question A: Find an approximate equation h(t)= ab^t of the exponential curve that contains the points (0,1.24) and (4,0.64).
Question B: Find the exponential regression equation.
Question C: Use r to estimate the percentage rate of decay of revenues from the electronic device.
Question D: Use r to estimate the revenue from the electronic device in 2012.
PLEASE HELP ME TO SOLVE THE PROBLEM! I HAVE BEEN STUCK ON THIS PROBLEM FOR A LONG TIME! AND PLEASE SHOW WORK, SO I CAN UNDERSTAND IT!!
THANK YOU SO MUCH!!
Found 2 solutions by Fombitz, ewatrrr:
Answer by Fombitz(32388) About Me  (Show Source):
You can put this solution on YOUR website!
A)h%280%29=ab%5E%280%29=1.24
a=1.24
.
.
h%284%29=1.24b%5E4=0.64
b%5E4=0.64%2F1.24
b=0.848
.
.
h%28t%29=1.24%280.848%29%5Et
.
.
Exponential regression data fitting is beyond the scope of this site.
I used the Hofstra regression equation utility at http://people.hofstra.edu/stefan_waner/realworld/newgraph/regressionframes.html to get
h=1.25406%280.839387%29%5Et with r=-0.985787

Answer by ewatrrr(24785) About Me  (Show Source):
You can put this solution on YOUR website!
 

Hi,

 approximate equation h(t)= ab^t  h(t) = 1.24(.8476)^t

a(b)^0 = 1.24, a+=+1.24 

%281.24%29b%5E4+=+.64, b =root%284%2C%28.64%2F1.24%29%29+=++.8476  

exponential regression equation(Used on-line calculator to find, may use TI) 

Y = 1.0124(.9268)^t

(recommend using Your TI as the best source for classroom work)

Using above to estimate the percentage rate of decay of revenues: 

1 + r = .9268, rate of decay = -.0732

h(12) =+1.0124%28.9268%29%5E12



Note: this is the linear regression line = -.159x + 1.23  for points given

done in Excel