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katrin [286]
3 years ago
11

Bethany,Lauren,Amanda,and David all meet at Family reunion. They are comparing their ages. They have found that Laura is 13 year

s older than Metheny and David is 11 years older than Amanda. They also found that the product of Bethany and Laura Sage is equal to twice and Amanda's age.Also, if they subtract 20 years from both Bethany's and Louren's age, the product is equal to David's age.
If x represents Bethany's age y represents Amanda's age, then which of the following system of equations can be used to determine the age of all for family members based on their findings?

Mathematics
1 answer:
bazaltina [42]3 years ago
7 0
The second system of equations, 

\left \{ {{y=\frac{x^2}{2}+\frac{13}{2}x} \atop {y=x^2-27x+129}}
is correct.

We know that Bethany's age is x.  Since Laura is 13 years older, her age is x+13.  The product of their ages is equal to twice Amanda's age, and Amanda's age is y.  This gives us:
x(x+13) = 2y

Using the distributive property, we have 
x²+13x=2y

Dividing everything by 2 (to isolate y), we have:
x²/2 + (13/2)x = y

If we take 20 years off of Bethany's age, it is now represented as x-20.  Taking 20 years off of Laura's age would be (x+13-20) or x-7.  The product of their ages now is equal to David's age; David is 11 years older than Amanda, so his age is y+11.  This gives us:

(x-20)(x-7)=y+11

Multiplying the binomials we have:"
x*x - 7*x - 20*x - 20(-7) = y+11
x²-7x-20x--140=y+11
x²-27x+140=y+11

To isolate y, subtract 11 from both sides:
x²-27x+140-11 = y+11-11
x²-27x+129 = y
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Answer:

a) P(X < 99) = 0.2033.

b) P(98 < X < 100) = 0.4525

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 of 100 and variance of 36.

This means that \mu = 100, \sigma = \sqrt{36} = 6

Sample of 25:

This means that n = 25, s = \frac{6}{\sqrt{25}} = 1.2

(a) P(X<99)

This is the pvalue of Z when X = 99. So

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

By the Central Limit Theorem

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

Z = \frac{99 - 100}{1.2}

Z = -0.83

Z = -0.83 has a pvalue of 0.2033. So

P(X < 99) = 0.2033.

b) P(98 < X < 100)

This is the pvalue of Z when X = 100 subtracted by the pvalue of Z when X = 98. So

X = 100

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

Z = \frac{100 - 100}{1.2}

Z = 0

Z = 0 has a pvalue of 0.5

X = 98

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

Z = \frac{98 - 100}{1.2}

Z = -1.67

Z = -1.67 has a pvalue of 0.0475

0.5 - 0.0475 = 0.4525

So

P(98 < X < 100) = 0.4525

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Answer:

Every day, the mass of the sunfish is multiplied by a factor of <u>[ln(1.34)/6]. </u>

<u></u>

Step-by-step explanation:

You have the following function:

M(t)=(1.34)^{\frac{t}{6}+4}

To know what is the factor that multiplies the mass of the sunfish each day, you derivative the function M(t):

\frac{dM(t)}{dt}=(1.34)^{\frac{t}{6}+4}(\frac{1}{6})ln(1.34)\\\\\frac{dM(t)}{dt}=\frac{ln(1.34)}{6}[(1.43)^{\frac{t}{6}+4}]\\\\\frac{dM(t)}{dt}=\frac{ln(1.34)}{6}M(t)  (1)

where you have used the following general derivative:

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