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3 years ago

Determine the interval(s) on which the function is (strictly) decreasing.

Mathematics

2 answers:

ANEK [815]3 years ago

5 0

The intervals where the function are strictly decresing are (-3, -2) ∪ (4, 6)

Luda [366]3 years ago

5 0

It's strictly increasing on: [-7,-6]∪[1,3].
<span>It's increasing on: [-7,-2]∪[1,3].</span>

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What is the exponential regression equation that fits these data? y x 1 4 2 8 3 27 4 85 5 250 6 600

Volgvan

Answer:

its is C because the other ones are obvious wrong. So it has to be C plus i did this test.

Step-by-step explanation:

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3 years ago

The quantity demanded x for a product is inversely proportional to the cube of the price p for

Harrizon [31]

X = k/p^3
125 = k/10^3 = k/1000
1000 x 125 = k
k = 125000

x = 125000/p^3

The profit is given by G = px - (125 + 2x) = p(125000/p^3) - 125 - 2(125000/p^3) = 125000/p^2 - 250000/p^3 - 125
For maximum profit:
dG/dp = 0
dG/dp = -250000/p^3 + 750000/p^4 = 0
750000 - 250000p = 0
p = 750000/250000 = 3

Therefore the price that will yeaild maximum profit is $3.

6 0

4 years ago

In college basketball, a shot made from beyond a designated arc radiating about 20 ft from the basket is worth three points ins

denis-greek [22]

Answer:

a) By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b) 4.02 standard deviations below the mean.

c) Making 25 or less shots has a pvalue of -4.02. Z-scores lower than -2 are considered surprising, so yes, it would be surprising for him to make only 25 of these shots.

Step-by-step explanation:

To solve this question, we are going to 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.

For proportions, we have that the mean is $\mu = p$ and the standard deviation is $s = \sqrt{\frac{p(1-p)}{n}}$

In this problem, we have that:

$p = 0.45, n = 100$

a)By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b)This is Z when X = 0.25.

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

By the Central Limit Theorem

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