The difference of two numbers is 15, and their quotient is 6. what are the two numbers

amm1812

Answer: x=7.21

Step-by-step explanation: This is a right triangle- remember the Pythagorean theorem: a² + b² = c². To find leg a, you'd use a = √(c² - b²) **leg a would be the side that is labeled with 12. To find leg b, you'd use b = √(c² - a²) *this is the equation we need. To find the hypotenuse, or <em>c</em>, you'd use c = √(a² + b²). This equation works for right triangles only.

Hope this helps :)

4 0

3 years ago

Please help asap

natima [27]

See the attached picture for the answers.

5 0

3 years ago

it is known that the population proton of utha residnet that are members of the church of jesus christ 0l6 suppose a random samp

Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

Proportion of 0.6

This means that $p = 0.6$

Sample of 46

This means that $n = 46$

Mean and standard deviation:

$\mu = p = 0.6$

$s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6*0.4}{46}} = 0.0722$

Probability of obtaining a sample proportion less than 0.5.

p-value of Z when X = 0.5. So

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{0.5 - 0.6}{0.0722}$

$Z = -1.38$

$Z = -1.38$ has a p-value of 0.0838

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

8 0

3 years ago

What is the definition of exponential decay?

tresset_1 [31]

Answer:

Exponential Decay -

A quantity is subject to exponential decay if it decreases at a rate proportional to its current value.

Step-by-step explanation:

Hope this answered your question ^^

8 0

3 years ago

Read 2 more answers

A box contains

Usimov [2.4K]

<span>the probability that a pen from the first box is selected
= total number of pens in 1st box/total number of objects in box 1
= 5/12

</span>the probability that a crayon from the second box is selected
= total number of crayons in 2nd box/total number of objects in box 2
= 6/8 = 3/4

7 0

3 years ago