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ella [17]
3 years ago
11

The average annual cost of the first year of owning and caring for a cat is $1,500. A sample of 81 will be used. Based on past s

tudies, the population standard deviation is assumed known with σ = $198. What is the margin of error for a 95% confidence interval of the mean cost of the first year of owning and caring for a cat?
Mathematics
1 answer:
Hunter-Best [27]3 years ago
7 0

Answer:

The margin of error for a 95% confidence interval of the mean cost of the first year of owning and caring for a cat is of $43.12.

Step-by-step explanation:

We have that to find our \alpha level, that is the subtraction of 1 by the confidence interval divided by 2. So:

\alpha = \frac{1 - 0.95}{2} = 0.025

Now, we have to find z in the Ztable as such z has a pvalue of 1 - \alpha.

That is z with a pvalue of 1 - 0.025 = 0.975, so Z = 1.96.

Now, find the margin of error M as such

M = z\frac{\sigma}{\sqrt{n}}

In which \sigma is the standard deviation of the population and n is the size of the sample.

Sample of 81

This means that n = 81

What is the margin of error for a 95% confidence interval of the mean cost of the first year of owning and caring for a cat?

M = z\frac{\sigma}{\sqrt{n}}

M = 1.96\frac{198}{\sqrt{81}}

M = 43.12

The margin of error for a 95% confidence interval of the mean cost of the first year of owning and caring for a cat is of $43.12.

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Solve for e.<br> 0.75(8 + e) = 2 - 1.25e
timofeeve [1]

Answer:

e = -2

Step-by-step explanation:

Well to solve for e in the following equation,

.75(8 + e) = 2 - 1.25e

We need to distribute and use the communicative property to find <em>e</em>.

6 + .75e = 2 - 1.25e

-2 to both sides

4 + .75e = -1.25e

-.75 to both sides

4 = -2e

-2 to both sides

e = -2

<em>Thus,</em>

<em>e is -2.</em>

<em />

<em>Hope this helps :)</em>

3 0
4 years ago
A presidential candidate's aide estimates that, among all college students, the proportion who intend to vote in the upcoming el
inessss [21]

Answer:

z=\frac{0.529 -0.6}{\sqrt{\frac{0.6(1-0.6)}{240}}}=-2.24  

p_v =P(z  

If we compare  the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 1% of significance the proportion college students expressed an intent to vote is not higher than 0.6

Step-by-step explanation:

Assuming the following question: A presidential candidate's aide estimates that, among all college students, the proportion p who intend to vote in the upcoming election is at least 60% . If 127 out of a random sample of 240 college students expressed an intent to vote, can we reject the aide's estimate at the 0.1 level of significance?

Data given and notation

n=240 represent the random sample taken

X=127 represent the college students expressed an intent to vote

\hat p=\frac{127}{240}=0.529 estimated proportion of college students expressed an intent to vote

p_o=0.6 is the value that we want to test

\alpha=0.01 represent the significance level

Confidence=99% or 0.99

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that at least 60% of students are intented to vote .:  

Null hypothesis:p \geq 0.6  

Alternative hypothesis:p < 0.6  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.529 -0.6}{\sqrt{\frac{0.6(1-0.6)}{240}}}=-2.24  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level provided \alpha=0.01. The next step would be calculate the p value for this test.  

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

p_v =P(z  

If we compare  the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 1% of significance the proportion college students expressed an intent to vote is not higher than 0.6

7 0
3 years ago
Use mathematical induction to prove that the statement is true for every positive integer n. Show your work.
never [62]
My first reasoning is the fact that the main number is 2
2nd reasoning is that 
2 x n = 4 
then 4 - 2 = 2
2 + 2 = 4 
4 is a factor of 2
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50 more than ___ is 64.
Sloan [31]

50 more than 14 is 64

14 + 50 = 64

Hope this helps

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vivado [14]

answer is D

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