AnswersFL-1200330-Algebra 2 CRModeling with Exponential and Logarithmic Equations

Modeling with Exponential and Logarithmic Equations Answers

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function would be most suitable to model these data.

A
A logarithmic
B
An exponential
C
A linear
D
A quadratic
4

and b =

Answer:

1.106

6

Did the water lilies double?

Answer not available
8

The graph to the right shows what you should have gotten on the regression calculator. Check all statements below that accurately describe the regression equation.

A
Some points do not lie on the regression curve, so it is not a good model.
B
Most points lie on or near the regression curve, so it is a good model.
C
The equation can be used to analyze the population growth, and to estimate values outside of what was collected.
9

In terms of the water lily population change, the value 3.915 represents:

Answer:

The initial number of water lilies, approximately 4, which matches the data.

10

Which two equations below could you solve to find D, the number of days it takes the water lily population to double?

A
2 = 3.915(1.106)D
B
7.830 = 3.915(1.106)D
C
7.830 = 3.915(2)D
D
2 = 1.106D
13

The value 1.106 represents:

Answer:

The daily growth factor is 1.106, meaning the water lily population grows by 10.6% each day.

16

Which solution method did you use?

A
Logarithms
B
Graphing y = 3.915(1.106)x and tracing
C
Graphing y = 3.915(1.106)x and y = 400, then finding the x-value of the intersection
17

Which of the following did you include in your description?

A
The value of 3.915 is the initial number of water lilies.
B
It is approximately 4, which matches the data.
C
The value 1.106 is the growth rate.
D
The rate represents growth for each day.
E
The percentage growth each day is 10.6%
18

Did the water lilies double?

Answers:
Selection 1:Yes
Selection 2:Approximately
19

By the 46th day, there are 400 water lilies in the pond. The estimate you made

A
close to 46 (or exactly right) because it was estimated well.
B
too low because the quick exponential growth was not accounted for.
C
too high because the exponential growth was overestimated.

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