Welp im kinda stuck and i just woke up so i cant think lol please help

Plz help me plzz i beg of u

Stells [14]

Answer:

2.0 x 10^11

Step-by-step explanation:

2.6 divide it by 1.3 and get 2.0. 9+2 = 11. Together with the, it would be 10^11. That how I got 2.0 x 10^11

Hope this Helps, have a nice day!

:)

7 0

3 years ago

*NEED ANSWER QUICK!!*

Rom4ik [11]

Answer:

You would need 9/4 or 2 1/4 gallons of paint

Step-by-step explanation:

You would need 2 1/4 gallon of paint because if 1/3 of the room takes 1/4 paint, then 3/4 would finish a room, multiply the three by three for three rooms and there you have 9/4 or 2 1/4 gallons

6 0

2 years ago

A grocery store’s receipts show that Sunday customer purchases have a skewed distribution with a mean of 27$ and a standard devi

34kurt

Answer:

(a) The probability that the store’s revenues were at least $9,000 is 0.0233.

(b) The revenue of the store on the worst 1% of such days is $7,631.57.

Step-by-step explanation:

According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and we take appropriately huge random samples (n ≥ 30) from the population with replacement, then the distribution of the sum of values of X, i.e ∑X, will be approximately normally distributed.

Then, the mean of the distribution of the sum of values of X is given by,

$\mu_{X}=n\mu$

And the standard deviation of the distribution of the sum of values of X is given by,

$\sigma_{X}=\sqrt{n}\sigma$

It is provided that:

$\mu=\$27\\\sigma=\$18\\n=310$

As the sample size is quite large, i.e. n = 310 > 30, the central limit theorem can be applied to approximate the sampling distribution of the store’s revenues for Sundays by a normal distribution.

(a)

Compute the probability that the store’s revenues were at least $9,000 as follows:

$P(S\geq 9000)=P(\frac{S-\mu_{X}}{\sigma_{X}}\geq \frac{9000-(27\times310)}{\sqrt{310}\times 18})\\\\=P(Z\geq 1.99)\\\\=1-P(Z$

Thus, the probability that the store’s revenues were at least $9,000 is 0.0233.

(b)

Let s denote the revenue of the store on the worst 1% of such days.

Then, P (S < s) = 0.01.

The corresponding z-value is, -2.33.

Compute the value of s as follows:

$z=\frac{s-\mu_{X}}{\sigma_{X}}\\\\-2.33=\frac{s-8370}{316.923}\\\\s=8370-(2.33\times 316.923)\\\\s=7631.56941\\\\s\approx \$7,631.57$

Thus, the revenue of the store on the worst 1% of such days is $7,631.57.

5 0

2 years ago

Many states run lotteries to raise money. A website advertises that it knows "how to increase YOUR chances of Winning the Lott

Crank

Complete question is;

Many states run lotteries to raise money. A website advertises that it knows "how to increase YOUR chances of Winning the Lottery." They offer several systems and criticize others as foolish. One system is called Lucky Numbers. People who play the Lucky Numbers system just pick a "lucky" number to play, but maybe some numbers are luckier than others. Let's use a simulation to see how well this system works. To make the situation manageable, simulate a simple lottery in which a single digit from 0 to 9 is selected as the winning number. Any value can be picked, but for this exercise, pick 1 as the lucky number. What proportion of the time do you win?

Answer:

10%

Step-by-step explanation:

We are told that To make the situation manageable, simulate a simple lottery in which a single digit from 0 to 9 is selected as the winning number.

This means the total number of single digits that could possibly be a winning one is 10.

Since we are told that only 1 can be picked, thus;

Probability of winning is; 1/10 = 0.1 or 10%

5 0

3 years ago

Polygon BCDE (is congruent to) RSTU find the value of y.

german

Y=14
If they are congruent then t=d so write the equation and solve from there, welcome im Procrastinating.

3 0

3 years ago