Total mobile data traffic. The following graph shows the predicted monthly mobile data traffic for the years 2013–2018. Use these data in Exercises 25 and 26. MOBILE DATA TRAFFIC a. Find an exponential function, base e , that fits the data, using the points ( 0 , 1.5 ) and ( 2 , 4.4 ) . Let x represent the number of years since 2013. b. Estimate the total monthly mobile data traffic in 2019 and 2022. c. When will total monthly mobile data traffic exceed 50 exabytes? d. What is the doubling time for total monthly traffic? e. Compare your answers with those from parts (c) – (e) of Exercise 25. Decide which exponential function seems to fit the data better, and explain why.
Total mobile data traffic. The following graph shows the predicted monthly mobile data traffic for the years 2013–2018. Use these data in Exercises 25 and 26. MOBILE DATA TRAFFIC a. Find an exponential function, base e , that fits the data, using the points ( 0 , 1.5 ) and ( 2 , 4.4 ) . Let x represent the number of years since 2013. b. Estimate the total monthly mobile data traffic in 2019 and 2022. c. When will total monthly mobile data traffic exceed 50 exabytes? d. What is the doubling time for total monthly traffic? e. Compare your answers with those from parts (c) – (e) of Exercise 25. Decide which exponential function seems to fit the data better, and explain why.
Solution Summary: The author explains how to calculate the exponential function with base e that fits the data.
The following graph shows the predicted monthly mobile data traffic for the years 2013–2018. Use these data in Exercises 25 and 26.
MOBILE DATA TRAFFIC
a. Find an exponential function, base e, that fits the data, using the points
(
0
,
1.5
)
and
(
2
,
4.4
)
. Let x represent the number of years since 2013.
b. Estimate the total monthly mobile data traffic in 2019 and 2022.
c. When will total monthly mobile data traffic exceed 50 exabytes?
d. What is the doubling time for total monthly traffic?
e. Compare your answers with those from parts (c) – (e) of Exercise 25. Decide which exponential function seems to fit the data better, and explain why.
Taylor Series Approximation Example- H.W
More terms used implies better approximation
f(x) 4
f(x)
Zero order
f(x + 1) = f(x;)
First order
f(x; + 1) = f(x;) + f'(x;)h
1.0
Second order
0.5
True
f(x + 1) =
f(x) + f'(x)h +
ƒ"(x;)
h2
2!
f(x+1)
0
x; = 0
x+1 = 1
x
h
f(x)=0.1x4-0.15x³- 0.5x2 -0.25x + 1.2
51
Taylor Series Approximation H.w:
Smaller step size implies smaller error
Errors
f(x) +
f(x,)
Zero order
f(x,+ 1) = f(x)
First order
1.0
0.5
Reduced step size
Second order
True
f(x + 1) = f(x) + f'(x)h
f(x; + 1) = f(x) + f'(x)h + "(xi) h2
f(x,+1)
O
x₁ = 0
x+1=1
Using Taylor Series Expansion estimate f(1.35) with x0 =0.75 with 5
iterations (or & s= 5%) for
f(x)=0.1x 0.15x³-0.5x²- 0.25x + 1.2
52
Could you explain this using the formula I attached and polar coorindates
Could you explain this using the formula I attached and polar coordinates
Chapter 3 Solutions
Calculus and Its Applications Plus MyLab Math with Pearson eText -- Access Card Package (11th Edition) (Bittinger, Ellenbogen & Surgent, The Calculus and Its Applications Series)
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