Use the functions f(x) and g(x) to answer the question.

weqwewe [10]

Answer:

-4 - 17x

Step-by-step explanation:

Anything enclosed in parentheses must be done first if possible. (3x + 2) is inside two sets of parentheses, but nothing can be done with 3x + 2.

Multiplication must be done next. [6(3x+2)-x] becomes 18x + 12 - x, or

17x + 12.

Now we have 4 - 17x - 12 + 4. Combining like terms through addition and subtraction, we get 4 - 12 + 4 - 17x, or -4 - 17x.

3 0

2 years ago

While he hikes in the Gold Country of northern California, Sid dreams about the adventurers that walked the same trails years ag

olga2289 [7]

I did. Undestand the probelm

5 0

2 years ago

What is the ratio 15 to 35 written as a fraction in lowest terms?

dmitriy555 [2]

B 3/7 because 15 divided by 5 = 3 and 35 divided by 5 = 7

4 0

2 years ago

Read 2 more answers

The mean of a population is 74 and the standard deviation is 15. The shape of the population is unknown. Determine the probabili

Lena [83]

Answer:

a) 0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

b) 0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c) 0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

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