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During this same time, the digital print manager tracked the number of visits to the website's homepage. He found that before launching the new marketing plan, there were 4,800 visits. Over the course of the next 5 weeks, the number of site visits increased by a factor of 1.5 each week.

Write an equation to model the relationship between the number of weeks, [tex]\( x \)[/tex], and the number of site visits, [tex]\( f(x) \)[/tex].

[tex]\( f(x) = a(b)^x \)[/tex]

Replace [tex]\( a \)[/tex] and [tex]\( b \)[/tex] with their correct values.


Sagot :

To solve this problem, we need to model the relationship between the number of weeks, [tex]\( x \)[/tex], and the number of site visits, [tex]\( f(x) \)[/tex]. The problem provides us with two key pieces of information:

1. The initial number of visits before launching the new marketing plan was 4,800.
2. The number of site visits increased by a factor of 1.5 each week.

The general form of the exponential growth model is:
[tex]\[ f(x) = a(b)^x \][/tex]

Here, [tex]\( a \)[/tex] represents the initial quantity (the number of visits at the beginning, i.e., at [tex]\( x = 0 \)[/tex]), and [tex]\( b \)[/tex] represents the growth factor per time period (in this case, per week).

Given the information:

- The initial number of visits, [tex]\( a \)[/tex], is 4800.
- The growth factor, [tex]\( b \)[/tex], is 1.5.

Substituting these values into the equation, we get:
[tex]\[ f(x) = 4800(1.5)^x \][/tex]

Thus, the equation that models the relationship between the number of weeks, [tex]\( x \)[/tex], and the number of site visits, [tex]\( f(x) \)[/tex], is:
[tex]\[ f(x) = 4800(1.5)^x \][/tex]
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