Please help me with this question.

PLEASE HELP !! ILL GIVE BRAINLIEST *EXTRA 40 POINTS* DONT SKIP :(( .!

Y_Kistochka [10]

53 and 17

Step-by-step explanation:

If you add 53 and 17, you get 70.

If you subtract 17 from 53, you get 36. Hope this helps!

7 0

3 years ago

Gia is painting her wall. 1 liter of paint can cover 10 square meters. She has a rectangular wall that

garik1379 [7]

5*4 equals 20 so her wall is 20 square meters
Given that one litre can cover 10 square meters, she needs 2 litres of paint to cover the wall

7 0

3 years ago

What is the midpoint of EC ?

sladkih [1.3K]

<u>Given</u>:

Given that the graph OACE.

The coordinates of the vertices OACE are O(0,0), A(2m, 2n), C(2p, 2r) and E(2t, 0)

We need to determine the midpoint of EC.

<u>Midpoint of EC:</u>

The midpoint of EC can be determined using the formula,

$Midpoint=(\frac{x_1+x_2}{2}, \frac{y_1+y_2}{2})$

Substituting the coordinates E(2t,0) and C(2p, 2r), we get;

$Midpoint=(\frac{2t+2p}{2},\frac{0+2r}{2})$

Simplifying, we get;

$Midpoint=(\frac{2(t+p)}{2},\frac{2r}{2})$

Dividing, we get;

$Midpoint=(t+p,r)$

Thus, the midpoint of EC is (t + p, r)

Hence, Option A is the correct answer.

4 0

3 years ago

A traveling salesman figures it costs 28

Strike441 [17]

I can use the equation .28(m) to solve this problem. If we plug in our numbers, we will get .28(315). This will give us 88.2. 88.2 is $88.2 dollars. Therefore, it costs him $88.2 dollars a week.

7 0

3 years ago

The amounts of electricity bills for all households in a city have a skewed probability distribution with a mean of $139 and a

ZanzabumX [31]

Answer:

P (within $6 of 4) = 0.9164

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 zscore 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 pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .

Mean of $139 and a standard deviation of $30.

This means that $\mu = 139, \sigma = 30$

Random sample of 75 households

This means that $n = 75, s = \frac{30}{\sqrt{75}} = 3.464$

75 > 30, which means that the sampling distribution is approximately normal.

Find the probability that the mean amount of electric bills for a random sample of 75 households selected from this city will be within $6 of the population mean.

This is the pvalue of Z when X = 139 + 6 = 145 subtracted by the pvalue of Z when X = 139 - 6 = 133.

X = 145

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

By the Central Limit Theorem

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