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anastassius [24]
4 years ago
9

a recipe calls for 6 cups of brown sugar for every 2 cups of white sugar. How many cups of brown sugar is required for every cup

of white sugar ​
Mathematics
1 answer:
sammy [17]4 years ago
3 0

Answer:

You need 3 cups of brown sugar for every 1 cup of white sugar.

Step-by-step explanation:

To find the smallest amount possible, divide both numbers by the smaller number. So, 6 (the amount of brown sugar) Divided by 2 equals 3, and 2 (the amount of white sugar) Divided by 2 equals 1.

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Simplify the expression <br> (Show work if you can)
Alborosie
This equation can be written as

(v-8)(v+5)/ (v-8)(v-3)
= v+5/v-3

4 0
3 years ago
Andrew plans to retire in 32 years. He plans to invest part of his retirement funds in stocks, so he seeks out information on pa
Debora [2.8K]

Answer:

a) 0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

b) 0.4129 = 41.29% probability that the mean return will be less than 8%

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}}.

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

Mean 8.7% and standard deviation 20.2%.

This means that \mu = 8.7, \sigma = 20.2

40 years:

This means that n = 40, s = \frac{20.2}{\sqrt{40}}

(a) What is the probability (assuming that the past pattern of variation continues) that the mean annual return on common stocks over the next 40 years will exceed 13%?

This is 1 subtracted by the pvalue of Z when X = 13. So

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

By the Central Limit Theorem

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

Z = \frac{13 - 8.7}{\frac{20.2}{\sqrt{40}}}

Z = 1.35

Z = 1.35 has a pvalue of 0.9115

1 - 0.9115 = 0.0885

0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

(b) What is the probability that the mean return will be less than 8%?

This is the pvalue of Z when X = 8. So

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

Z = \frac{8 - 8.7}{\frac{20.2}{\sqrt{40}}}

Z = -0.22

Z = -0.22 has a pvalue of 0.4129

0.4129 = 41.29% probability that the mean return will be less than 8%

8 0
3 years ago
How many quarters make a whole​
Eduardwww [97]

Answer:

4

Step-by-step explanation:

4×(1/4) = 1

⁄(⁄ ⁄•⁄ω⁄•⁄ ⁄)⁄

3 0
3 years ago
Two circles have radii of 4 units and 6 units. What is the radius of a circle whose area is equal to the sum of the areas of the
Bumek [7]

Answer:

Step-by-step explanation:

We that the area of a circle is Pi times r^2 where r is the radius

Let A be the area of the first circle and S the area of the second one and T the total one

A=4^2× Pi

S=6^2× Pi

T = Pi( 4^2 +6^2)

= Pi ( 16+36) = Pi× 52

52 is the radius square

So r = root square 52 = 2 root square 13

3 0
3 years ago
If you flip three fair coins, what is the probability that you'll get a tail on the first flip, a head on the secand flip. And a
DENIUS [597]

Answer:

Probability of getting {THT} is 0.125

Step-by-step explanation:

Since 3 fair coins are tossed  we can get the sample space for the experiment.

Sample space of the experiment = {HHH, HHT, HTT, HTH, TTH, THH, THT, TTT}

As per question ,

Getting Tail , Head, Tail is a success so all other events other than {THT} is a failure.

Therefore probability of getting {THT} = \frac{1}{8} = 0.125

3 0
3 years ago
Read 2 more answers
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