If D = Z + 6 and C = -2 + Z - Z^2, find an expression that equals 3D + C in standard form

Mathematics

1 answer:

kykrilka [37]3 years ago

6 0

Answer:

4Z+16-Z²

Step-by-step explanation:

Given that,

D = Z+6

C = -2 + Z - Z²

We need to find the value of 3D+C.

So,

3D+C = 3(Z + 6)+(-2 + Z - Z²)

= 3Z+18-2+Z-Z²

= 4Z+16-Z²

So, the required expression is 4Z+16-Z².

You might be interested in

y, in terms of time the rain fell, x. The time is measured in hours after 12:00 P.M., with x=0 corresponding to the time 12:

Lana71 [14]

Answer:

At the time measurement starts i.e. initially there was no rainfall i.e. y value is zero.

Step-by-step explanation:

y, in terms of time the rain fell, x.

Now, x is measured in hours after 12 : 00 P.M., with x = 0 corresponding to the time 12 : 00 P.M.

Therefore, the ordered pair (x,y) ≡ (0,0) means that at the time measurement starts i.e. at 12 : 00 P. M. there was no rainfall i.e. y value is zero. (Answer)

7 0

3 years ago

The elevation of city A is 96 feet below sea level; the elevation of city C is 24 feet below sea level. The elevation of city D

Mama L [17]

Arms B.B.cvv was tav gh

7 0

4 years ago

Jean works for the government and was conducting a survey to determine the income levels of a number of different neighborhoods

Brrunno [24]

Answer:

0.0418 = 4.18% probability that the average income level in the neighborhoods was less than $38,000.

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 $s = \frac{\sigma}{\sqrt{n}}$ .