Need help this is urgent!!!

you have $5.00 in quarters and dimes. you have a total of 41 coins. how many of the coins are quarters?

sweet [91]

So, from this information you can set up two equations:
0.1x + 0.25y = 5 dollars and
x + y = 41 coins
where x = how many dimes and y = how many quarters

Solve for either x or y in the second equation, so x = 41 - y and then plug this in for x in the first equation to get:
0.1(41 - y) + 0.25y = 5
4.1 - 0.1y + 0.25y = 5
4.1 + 0.15y = 5
0.15y = 0.9
y = 6
We solved for y and now we know there are 6 quarters, so you can plug this into the second equation to solve for x. We fine that we have 35 dimes. You can always your work by plugging what you get for x and y back into the equations.

3 0

3 years ago

An orange juice producer buys oranges from a large orange grove that has one variety of orange. The amount of juice squeezed fro

skad [1K]

Answer:

The probability is 70% that the sample mean amount of juice will be contained between 4.9168 ounces and 5.0832 ounces.

Step-by-step explanation:

To solve this question, the Normal probability distribution and the Central Limit Theorem are important.

Normal probability distribution

Problems of normally distributed samples 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $\frac{\sigma}{\sqrt{n}}$

In this problem, we have that:

$\mu = 5, \sigma = 0.4, n = 25, s = \frac{0.4}{\sqrt{25}} = 0.08$

The probability is 70% that the sample mean amount of juice will be contained between what two values symmetrically distributed around the population mean?

The lower end of this interval is the value of X when Z has a pvalue of 0.5 - 0.7/2 = 0.15

The upper end of this interval is the value of X when Z has a pvalue of 0.5 + 0.7/2 = 0.85

Lower end

X when Z has a pvalue of 0.15. So X when $Z = -1.04$ .