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3 years ago

What's median number for the numbers 4,8,10,5,9

2 answers:

5 0

4,5,8,9,10
First, in order to find the median you have to put each number in order from least to greatest.
Your median is the number in the middle.
In this case that number is 8.
If you have an even amount of numbers, you will have to convert that into a decimal.
Hopefully this has helped!

NemiM [27]3 years ago

4 0

Hey there!

Median means the middle number in a set of numbers. To find the median, we have to arrange all the numbers in order from least to greatest.

The order of numbers from least to greatest are:

4,5,8,9,10

The middle number in these set of numbers is 8. Therefore the median is 8.

Hope it helps! Thank you for being part of the Brainly Community!

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The data given to the right includes data from candies, and of them are red. The company that makes the candy claims that % of

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Using the z-distribution, the 95% confidence interval for the percentage of red candies is of (7.84%, 33.18%). Since 33% is part of the interval, there is not enough evidence to conclude that the claim is wrong.

<h3>What is a confidence interval of proportions?</h3>

A confidence interval of proportions is given by:

$\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}$

In which:

$\pi$ is the sample proportion.

z is the critical value.

n is the sample size.

In this problem, we have a 95% confidence level, hence $\alpha = 0.95$ , z is the value of Z that has a p-value of $\frac{1+0.95}{2} = 0.975$ , so the critical value is z = 1.96.

Researching this problem on the internet, 8 out of 39 candies are red, hence the sample size and the estimate are given by:

$n = 39, \pi = \frac{8}{39} = 0.2051$

Hence the bounds of the interval are:

$\pi - z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.2051 - 1.96\sqrt{\frac{0.2051(0.7949)}{39}} = 0.0784$

$\pi + z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.2051 + 1.96\sqrt{\frac{0.2051(0.7949)}{39}} = 0.3318$

As a percentage, the 95% confidence interval for the percentage of red candies is of (7.84%, 33.18%). Since 33% is part of the interval, there is not enough evidence to conclude that the claim is wrong.

More can be learned about the z-distribution at brainly.com/question/25890103

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