Un servicio de datos para clientes móviles presenta las siguientes variantes:

sergiy2304 [10]

Y=-2x+200 hope this helps

3 0

3 years ago

Can somebody explain to me how they got 3^4(x) = 3^3(x+2)? Then explain what happened to the 3 in 3^4 and the 3 in 3^3? Please a

musickatia [10]

Answer:

x=6

Step-by-step explanation:

81^x = 27 ^(x+2)

81 = 3^4 and 27 =3^3 so replace 81 and 27 in the equation

3^4^x = 3^3^(x+2)

When we have a power to a power we can multiply the exponents

a ^b^c = a^(b*c)

3^(4x) = 3^(3*(x+2))

Since the bases are the same, the exponents have to be the same

a^b = a^c means b=c

4x = 3(x+2)

Now we can solve for x

Distribute

4x = 3x+6

Subtract 3x from each side

4x-3x = 3x-3x+6

x = 6

3 0

3 years ago

A. 3<br> B. -3/4<br> C. -1<br> D. 2

yawa3891 [41]

B
because rise over run

6 0

2 years ago

Read 2 more answers

Fill in values for a, b and c so that the answer to this equation is x = 4.<br>a(bx+3)=c

den301095 [7]

Answer:

A=1, B=3, C=15

Step-by-step explanation:

I think that

1(3x+3)=15

3x+3=15

3x=12

x=4

7 0

2 years ago

The average Act score follows a normal distribution, with a mean of 21.1 and a standard deviation of 5.1. What is the probabilit

ohaa [14]

Answer:

0.43% probability that the mean IQ score of 50 randomly selected people will be more than 23

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 normally distributed samples are 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 $s = \frac{\sigma}{\sqrt{n}}$ .