5. What is the simplest way to write
1 answer:
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Answer:
- P(t) = 100·2.3^t
- 529 after 2 hours
- 441 per hour, rate of growth at 2 hours
- 5.5 hours to reach 10,000
Step-by-step explanation:
It often works well to write an exponential expression as ...
value = (initial value)×(growth factor)^(t/(growth period))
(a) Here, the growth factor for the bacteria is given as 230/100 = 2.3 in a period of 1 hour. The initial number is 100, so we can write the pupulation function as ...
P(t) = 100·2.3^t
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(b) P(2) = 100·2.3^2 = 529 . . . number after 2 hours
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(c) P'(t) = ln(2.3)P(t) ≈ 83.2909·2.3^t
P'(2) = 83.2909·2.3^2 ≈ 441 . . . bacteria per hour
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(d) We want to find t such that ...
P(t) = 10000
100·2.3^t = 10000 . . . substitute for P(t)
2.3^t = 100 . . . . . . . . divide by 100
t·log(2.3) = log(100)
t = 2/log(2.3) ≈ 5.5 . . . hours until the population reaches 10,000
Answer:
p-value: 0.0367
Decision: Reject H₀
Step-by-step explanation:
Hello!
Hypothesis to test:
H₀:ρ₁-ρ₂=0
H₁:ρ₁-ρ₂>0
The statistic to use to test the difference between two population proportions is the approximation of Z
Z=<u> (^ρ₁-^ρ₂)-(ρ₁-ρ₂) </u> ≈N(0;1)
√ (<u>^ρ₁(1-^ρ₁))/n₁)+(^ρ₂(1-^ρ₂)/n₂))</u>
Z=<u> (0.28-0.15)-0 </u>= 1.79
√ (<u>0.28(1-0.28)/200)+(0.15(1-0.15)/300)</u>
p-value
Remember: The p-value is defined as the probability corresponding to the calculated statistic if possible under the null hypothesis (i.e. the probability of obtaining a value as extreme as the value of the statistic under the null hypothesis).
P(Z>1.79)= 0.0367
Conclusion:
Comparing the p-value against the significance level, you can decide to reject the null hypothesis.
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