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Mathematics

1 answer:

noname [10]3 years ago

6 0

Answer:

Step-by-step explanation:

So lets use the process of elimantion to find the answer.

Firs off, we can tell that this is a greater/less than or equal to inequlaity, since there is a inclosed circle, not a open one. So this leaves the top left answer and bottem right answer.

Now, we can see that the graph is from 0-15. X is at 7.

This means its x+8, because the x would be smaller, or possibly even negatibe on this graph.

My theory that can better support my annwer is if we solve for x:

x+8=15

We can subtract 8 from both sides:

x=7

And as we can see on the inequality, x is at 7 in the graph.

Hope this makes sense and helps!

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There are 2,000 eligible voters in a precinct. A total of 500 voters are randomly selected and asked whether they plan to vote f

Ann [662]

Answer:

$0.7 - 2.58 \sqrt{\frac{0.7(1-0.7)}{500}}=0.647$

$0.7 + 2.58 \sqrt{\frac{0.7(1-0.7)}{500}}=0.753$

And the 99% confidence interval would be given (0.647;0.753).

So the correct answer would be:

a. 0.647 and 0.753

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The population proportion have the following distribution

$p \sim N(p,\sqrt{\frac{p(1-p)}{n}})$

Solution to the problem

The estimated population proportion for this case is:

$\hat p = \frac{350}{500}=0.7$

The confidence interval would be given by this formula

$\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}$

For the 99% confidence interval the value of $\alpha=1-0.99=0.01$ and $\alpha/2=0.005$ , with that value we can find the quantile required for the interval in the normal standard distribution.