QUESTION IMAGE
Question
over time, the number of organisms in a population increases exponentially. the following table shows the approximate number of organisms after ( y ) years.
| ( y ) years | number of organisms, ( n ) |
|---|---|
| 2 | 60 |
| 3 | 67 |
| 4 | 75 |
the environment in which the organism lives can support at most 600 organisms. assuming the trend continues, after how many years will the environment no longer be able to support the population?
options: 82, 61, 12, 24
Step1: Identify the exponential model
The general form of an exponential function is \( n = ab^y \), where \( a \) is the initial value, \( b \) is the growth factor, \( y \) is the number of years, and \( n \) is the number of organisms. We can use the given data points to find \( a \) and \( b \). Let's start with the first two points \((1, 55)\) and \((2, 60)\).
For \( y = 1 \), \( n = 55 \): \( 55 = ab^1 \implies ab = 55 \)
For \( y = 2 \), \( n = 60 \): \( 60 = ab^2 \)
Divide the second equation by the first: \( \frac{ab^2}{ab} = \frac{60}{55} \implies b = \frac{60}{55} \approx 1.0909 \)
Then from \( ab = 55 \), \( a = \frac{55}{b} \approx \frac{55}{1.0909} \approx 50.42 \)
Let's check with the third point \((3, 67)\). Using the model \( n = 50.42(1.0909)^3 \approx 50.42(1.0909 \times 1.0909 \times 1.0909) \approx 50.42(1.295) \approx 65.3 \), which is close to 67 (considering possible rounding).
Step2: Solve for \( y \) when \( n = 600 \)
We have the model \( n = 50.42(1.0909)^y \). We need to find \( y \) when \( n = 600 \).
So, \( 600 = 50.42(1.0909)^y \)
Divide both sides by 50.42: \( \frac{600}{50.42} \approx 11.9 \approx (1.0909)^y \)
Take the natural logarithm of both sides: \( \ln(11.9) \approx y \ln(1.0909) \)
We know that \( \ln(11.9) \approx 2.47 \) and \( \ln(1.0909) \approx 0.087 \)
Then \( y \approx \frac{2.47}{0.087} \approx 28.4 \). Wait, this doesn't match the options. Maybe we made a mistake in the model. Alternatively, let's check the growth rates between consecutive years:
From year 1 to 2: \( \frac{60 - 55}{55} \approx 0.0909 \)
Year 2 to 3: \( \frac{67 - 60}{60} \approx 0.1167 \)
Year 3 to 4: \( \frac{75 - 67}{67} \approx 0.1194 \)
The growth rate is increasing, but maybe we can use a different approach. Let's list the number of organisms and see the pattern:
Year 1: 55
Year 2: 60 (increase by 5)
Year 3: 67 (increase by 7)
Year 4: 75 (increase by 8)
Wait, maybe it's better to use the exponential regression feature (if we consider a calculator approach). Alternatively, let's test the options:
For \( y = 12 \):
Let's calculate the number of organisms step by step with approximate growth.
Year 1: 55
Year 2: 55 + 5 = 60
Year 3: 60 + 7 = 67
Year 4: 67 + 8 = 75
Year 5: 75 + 10 = 85 (approximate growth, maybe the growth rate is around 10-15%? Wait, 55 to 60 is ~9%, 60 to 67 is ~11.6%, 67 to 75 is ~11.9%, 75 to 85 is ~13.3%, 85 to 97 is ~14.1%, 97 to 111 is ~14.4%, 111 to 127 is ~14.4%, 127 to 145 is ~14.2%, 145 to 166 is ~14.5%, 166 to 189 is ~13.9%, 189 to 215 is ~13.8%, 215 to 244 is ~13.5%, 244 to 277 is ~13.5%, 277 to 314 is ~13.3%, 314 to 355 is ~13.1%, 355 to 399 is ~12.4%, 399 to 447 is ~12.0%, 447 to 499 is ~11.6%, 499 to 554 is ~11.0%, 554 to 615 is ~11.0%. Wait, at year 12, maybe? Wait, the options are 82, 61, 12, 24. Wait, maybe my initial model was wrong. Let's try another way. Let's use the exponential function with the first point (1,55) and the ratio between consecutive terms.
The ratio between year 2 and year 1: 60/55 ≈ 1.0909
Year 3/year 2: 67/60 ≈ 1.1167
Year 4/year 3: 75/67 ≈ 1.1194
Let's take the average ratio: (1.0909 + 1.1167 + 1.1194)/3 ≈ (3.327)/3 ≈ 1.109
So the growth factor \( b \approx 1.11 \), initial value \( a = 55 / 1.11 ≈ 49.55 \)
Now, \( n = 49.55(1.11)^y \)
We need \( n = 600 \)
So, \( 49.55(1.11)^y = 600 \)
\( (1.11)^y = 600 / 49.55 ≈ 12.11 \)
Take log: \( y = \ln(12.11)/\ln(1.11) ≈ 2.492 / 0.1044 ≈ 23.87 \approx 24 \). Wait, 24 is an option. Wait, but let's check:
For \( y = 12 \): \( n = 49.55(1.11)^{12} \approx 49.55(3.498) ≈ 173 \),…
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