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vlada-n [284]
3 years ago
14

Valentino starts with a population of 1,500 amoebas that increases 35% in size every hour for a number of hours, h. The expressi

on 1,500(1+0.35)h finds the number of amoebas after h hours. Which statement about this expression is true?
A. It is the initial population raised to the growth factor after h hours.

B. It is the sum of the initial population and the percent increase.

C. It is the sum of the initial population and the growth factor after h hours.

D. It is the product of the initial population and the growth factor after h hours.
Mathematics
2 answers:
Ne4ueva [31]3 years ago
7 0

Answer:  It is the product of the initial population and the growth factor after h hours.

Step-by-step explanation:

Given: Valentino starts with a population of 1,500 amoebas that increases 35% in size every hour for a number of hours, h.

The expression 1,500(1+0.35)^h finds the number of amoebas after h hours.

On simplifying the above expression we get, 1,500(1.35)^h.

At h=0, the initial population of amoebas = 1,500

At h=1, the population of amoebas =1,500(1.35)

The growth factor = \frac{1,500(1.35)}{1500}=1.35

Hence, the expression 1,500(1+0.35)^h, is the product of the initial population and the growth factor after h hours.

JulsSmile [24]3 years ago
6 0

Answer:

Option D.

Step-by-step explanation:

The growth factor is (1 + 0.35)^h so 1500(1 + 0.35)^h is the product of initial population and the growth factor.

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Answer:

t=\frac{136-140}{\frac{11}{\sqrt{24}}}=-1.781    

p_v =P(t_{(23)}  

If we compare the p value and the significance level assumed \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the mean is less than 140 pounds at 5% of signficance.  

Step-by-step explanation:

Data given and notation  

\bar X=136 represent the sample mean

s=11 represent the sample standard deviation

n=24 sample size  

\mu_o =140 represent the value that we want to test

\alpha=0.01 represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the mean is less than 140, the system of hypothesis would be:  

Null hypothesis:\mu \geq 140  

Alternative hypothesis:\mu < 140  

If we analyze the size for the sample is < 30 and we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:  

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic

We can replace in formula (1) the info given like this:  

t=\frac{136-140}{\frac{11}{\sqrt{24}}}=-1.781    

P-value

The first step is calculate the degrees of freedom, on this case:  

df=n-1=24-1=23  

Since is a one left tailed test the p value would be:  

p_v =P(t_{(23)}  

Conclusion  

If we compare the p value and the significance level assumed \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the mean is less than 140 pounds at 5% of signficance.  

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