F(x) = 4x + 2; find f(8)

Help me plz with this I need help

marysya [2.9K]

How are we supposed to help with this what the heck??

4 0

3 years ago

Will give brainliest answer

nexus9112 [7]

Answer:

No

Step-by-step explanation:

The Triangle Inequality Theorem states that the sum of any 2 sides of a triangle must be greater than the measure of the third side.

We see that: 4.1 + 1.3 < 8.4

=> Can't form a triangle from 4.1 cm, 8.1 cm and 1.3 cm

5 0

3 years ago

Seven is at most the quotient of a number d and −5

kirill [66]

7 <= d/-5

hope it helps

8 0

3 years ago

The scores on the GMAT entrance exam at an MBA program in the Central Valley of California are normally distributed with a mean

Kaylis [27]

Answer:

58.32% probability that a randomly selected application will report a GMAT score of less than 600

93.51% probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600

98.38% probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600

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

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

In this problem, we have that:

$\mu = 591, \sigma = 42$

What is the probability that a randomly selected application will report a GMAT score of less than 600?

This is the pvalue of Z when X = 600. So

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

$Z = \frac{600 - 591}{42}$

$Z = 0.21$

$Z = 0.21$ has a pvalue of 0.5832

58.32% probability that a randomly selected application will report a GMAT score of less than 600

What is the probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600?

Now we have $n = 50, s = \frac{42}{\sqrt{50}} = 5.94$

This is the pvalue of Z when X = 600. So

$Z = \frac{X - \mu}{s}$

$Z = \frac{600 - 591}{5.94}$

$Z = 1.515$

$Z = 1.515$ has a pvalue of 0.9351

93.51% probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600

What is the probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600?

Now we have $n = 50, s = \frac{42}{\sqrt{100}} = 4.2$

$Z = \frac{X - \mu}{s}$

$Z = \frac{600 - 591}{4.2}$

$Z = 2.14$

$Z = 2.14$ has a pvalue of 0.9838

98.38% probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600

8 0

3 years ago

A young couple purchases their first new home in 2011 for $95,000. They sell it to move into a bigger home in 2018 for $105,00

mart [117]

Given:

The value of home in 2011 is $95,000.

The value of home in 2018 is $105,000.

To find:

The exponential model for the value of the home.

Solution:

The general exponential model is

$y=ab^x$ ...(i)

where, a is initial value and b is growth factor.

Let 2011 is initial year and x be the number of years after 2011.

So, initial value of home is 95,000, i.e., a=95,000.

Put a=95000 in (i).

$y=95000b^x$ ...(ii)

The value of home in 2018 is $105,000. It means the value of y is 105000 at x=7.

$105000=95000b^7$

$\dfrac{105000}{95000}=b^7$

$\dfrac{21}{19}=b^7$

Taking 7th root on both sides, we get

$\left(\dfrac{21}{19}\right)^{\frac{1}{7}}=b$

Put $b=\left(\dfrac{21}{19}\right)^{\frac{1}{7}}$ in (ii).

$y=95000\left(\left(\dfrac{21}{19}\right)^{\frac{1}{7}}\right)^x$

$y=95000\left(\dfrac{21}{19}\right)^{\frac{x}{7}}$

Therefore, the required exponential model for the value of home is $y=95000\left(\dfrac{21}{19}\right)^{\frac{x}{7}}$ , where x is the number of years after 2011.

5 0

3 years ago