Question 2 of 10<br> 2 Points<br> Which of the following is the solution to 4|x+32 8?

Select the equation that is equivalent to the equation: y+6=-4(X-2)

USPshnik [31]

First, you gotta distribute the -4 to x-2,

<span>y+6=-4(X-2)
y+6=-4x+8

Then, subtract both sides by 6,
y+6-6=-4x+8-6
y=-4x+2

Done</span>

7 0

3 years ago

Read 2 more answers

Know how to calculate sample size: A restaurant would like to estimate the average $ amount of a take-out order. The standard de

Ne4ueva [31]

Easy it’s c duhhhhhhh girl it’s C

8 0

2 years ago

Please help it's urgent.

arlik [135]

Answer:

It is the second triangle.

Step-by-step explanation:

This is because the area of the square is given as 25^2 as the perpendicular, 144^2 as the base, and the hypotenuse is 169^2.

Length of the perpendicular = 5^2 (Because 25^2 / 5^2)

Length of the base = 12^2

Length of the hypotenuse = 13^2

So, the Pythagoras theorem is,

=> $H^{2} = P^{2} + B^{2}$

=> $13^{2} =12^{2} +5^{2}$

This is true, because, 13*13 = 12*12 + 5*5

=> 169 = 144 + 25

=> 169 = 169

If my answer helped, kindly mark me as the brainliest!!

Thanks!!

3 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 $s = \sqrt{\frac{p(1-p)}{n}}$