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Sholpan [36]
2 years ago
7

Given the following exponential function, identify whether the change represents

Mathematics
1 answer:
Nookie1986 [14]2 years ago
4 0

The percentage rate of increase is 36.2% and the exponential function represent the growth.

<h3>What is an exponential function?</h3>

It is defined as the function that rapidly increases and the value of the exponential function is always a positive. It denotes with exponent \rm y = a^x

where 'a' is a constant and a>1

We have exponential function:

\rm y = 8900(1.362)^x

If we compare with

\rm y =a(1+r)^x

If 1+r > 1

1.362 > 1

So the growth rate r is

1 + r = 1.362

r = 0.362

r = 0.362×100

r = 36.2%

Thus, the percentage rate of increase is 36.2% and the exponential function represent the growth.

Learn more about the exponential function here:

brainly.com/question/11487261

#SPJ1

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Answer:

The null hypothesis is not rejected.

There is no enough evidence to support the claim that the CO level is lower  in non-smoking working areas compared to smoking work areas.

P-value = 0.07.

Step-by-step explanation:

We have to perform a test on the difference of means.

The claim that we want to test is that CO is less present in no-smoking work areas.

Then, the null and alternative hypothesis are:

H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2 > 0

being μ1: mean CO level in smoking work areas, and μ2: mean CO level in no-smoking work areas.

The significance level is assumed to be 0.05.

Smoking areas sample

Sample size n1=40.

Sample mean M1=11.6

Sample standard deviation s1=7.3

No-smoking areas sample

Sample size n2=40

Sample mean M2=6.9

Sample standard deviation s2=2.7

First, we calculate the difference between means:

M_d=M_1-M_2=11.6-7.3=4.3

Second, we calculate the standard error for the difference between means:

s_{M_d}=\sqrt{\dfrac{\sigma_1^2}{n_1}+\dfrac{\sigma_2^2}{n_2}}=\sqrt{\dfrac{7.3^2}{40}+\dfrac{2.7^2}{40}}=\sqrt{\dfrac{53.29+7.29}{40}}=\sqrt{\dfrac{60.58}{40}}\\\\\\s_{M_d}=\sqrt{1.5145}=1.23

Now, we can calculate the t-statistic:

t=\dfrac{M_d-(\mu_1-\mu_2)}{s_{M_d}}=\dfrac{4.3-0}{1.23}=3.5

The degrees of freedom are calculated with the Welch–Satterthwaite equation:

df=\dfrac{(\dfrac{s_1^2}{n_1}+\dfrac{s_2^2}{n_2})^2}{\dfrac{s_1^4}{n_1(n_1-1)}+\dfrac{s_2^4}{n_2(n_2-1)}} \\\\\\\\df=\dfrac{(\dfrac{7.3^2}{40}+\dfrac{2.7^2}{40})^2}{\dfrac{7.3^4}{40(39)}+\dfrac{2.7^4}{40(39)}} =\dfrac{(\dfrac{53.29}{40}+\dfrac{7.29}{40})^2}{\dfrac{2839.82}{1560}+\dfrac{53.14}{1560}} \\\\\\\\df=\dfrac{1.5145^2}{1.8545}=\dfrac{2.2937}{1.8545}=1.237

The P-value for this right tail test, with 1.237 degrees of freedom and t=3.5 is:

P-value=P(t>3.5)=0.07

The P-value is bigger than the significance level, so the effect is not significant. The null hypothesis is not rejected.

There is no enough evidence to support the claim that the CO level is lower  in non-smoking working areas compared to smoking work areas.

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Answer:

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Step-by-step explanation:

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Answer:

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