A delivery truck drove 203 mi in 3.5 h. After unloading and loading new cargo, it traveled on another 243 mi for 4.5 h.

For the diagram shown, which angles are alternate interior angles? ∠3 and ∠6 ∠8 and ∠2 ∠4 and ∠7 ∠3 and ∠5

Karolina [17]

Answer:

3 and 5

Step-by-step explanation:

Alternate interior angles are the angles in between the two lines and on the inside

4 and 6

3 and 5

6 0

3 years ago

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Solve for c 6/15=2/c

saul85 [17]

$\frac{6}{15}$ = $\frac{2}{c}$ Multiply both sides by 15
6 = $\frac{30}{c}$ Multiply both sides by c
6c = 30 Divide both sides by 6
c = 5

7 0

3 years ago

ALGEBRA QUESTION WILL GIVE BRAINLIEST IF CORRECT!!!

Ulleksa [173]

Answer:

Step-by-step explanation:

(f + g)(x) simply means that you are adding together the 2 functions that are written in terms of x.

$x^3-x+x^3+2x^2-10$

The only like terms we have there are the x-cubed's, so

$2x^3+2x^2-x-10=(f+g)(x)$

3 0

3 years ago

Help Would Be Appreciated!

ycow [4]

With an equation you must isolate x or whatever the variable is. Operations are the things used to make the difference like +,-,x,/.

A great example of this is the following

4x-12=0

First add 12 to both sides making the equation go to

4x=12

now divide 4 from both sides making

x=3

5 0

3 years ago

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Life Expectancies In a study of the life expectancy of people in a certain geographic region, the mean age at death was years an

Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

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

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

We have:

Mean $\mu$ , standard deviation $\sigma$ .

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

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

Find the probability that the mean life expectancy will be less than years.

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

8 0

2 years ago