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Jobisdone [24]
2 years ago
12

4. The perimeter of a triangle is 105 inches. The longest side is 22 inches longer than the shortest side. The sum of the

Mathematics
1 answer:
Cloud [144]2 years ago
3 0

Answer:

x = 45

y = 37

z = 23

Step-by-step explanation:

x + y + z = 105

x = z + 22

x + 15 = y + z

(z + 22) + 15 = y + z

              37 = y

           x + y + z = 105

(z + 22) + 37 + z = 105

                     2z = 46

                       z = 23

    x + y + z = 105

x + 37 + 23 = 105

               x = 45

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Answer:

z=\frac{13-20}{4}=-1.75

Assuming:

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Step-by-step explanation:

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

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The probability mass function for the Binomial distribution is given as:

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Where (nCx) means combinatory and it's given by this formula:

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If we appply the approximation the new mean and standard deviation are:

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Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  The letter \phi(b) is used to denote the cumulative area for a b quantile on the normal standard distribution, or in other words: \phi(b)=P(z

The z score is given by this formula:

z=\frac{x-\mu}{\sigma}

If we replace we got:

z=\frac{13-20}{4}=-1.75

Let's assume that we conduct the following test:

H0: \mu \geq 20

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We want to check is the score for the student is significantly less than the expected value using random guessing.

So on this case since we have the statistic we can calculate the p value on this way:

p_v = P(Z

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