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netineya [11]
3 years ago
9

A ball is shot into the air using a brand new super-high-tech robotic arm to help baseball players practice catch fly balls.

Mathematics
1 answer:
stepladder [879]3 years ago
6 0

Answer:

69 feet

Step-by-step explanation:

we have

h(t)=-16t^{2}+64t+5

where

h(t) is the height of the ball

t is the time in seconds

we know that the given equation is a vertical parabola open downward

The vertex is the maximum

so

the y-coordinate of the vertex represent the maximum height of the ball

Convert the quadratic equation into vertex form

The equation in vertex form is equal to

y=(x-h)^{2}+k

where

(h,k) is the vertex of the parabola

h(t)=-16t^{2}+64t+5

h(t)-5=-16t^{2}+64t

h(t)-5=-16(t^{2}-4t)

h(t)-5-64=-16(t^{2}-4t+4)

h(t)-69=-16(t^{2}-4t+4)

h(t)-69=-16(t-2)^{2}

h(t)=-16(t-2)^{2}+69

the vertex is the point (2,69)

therefore

The maximum height is 69 ft

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This is the correct answer, because ever since the transit system was made, car rides went down and down.

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A study of college football games shows that the number of holding penalties assessed has a mean of 2.2 penalties per game and a
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Answer:

5.71% probability that, for a sample of 40 college games to be played next week, the mean number of holding penalties will be 2 penalties per game or less

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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.

In this question, we have that:

\mu = 2.2, \sigma = 0.8, n = 40, s = \frac{0.8}{\sqrt{40}} = 0.1265

What is the probability that, for a sample of 40 college games to be played next week, the mean number of holding penalties will be 2 penalties per game or less

This is the pvalue of Z when X = 2. So

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

By the Central Limit Theorem

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

Z = \frac{2 - 2.2}{0.1265}

Z = -1.58

Z = -1.58 has a pvalue of 0.0571

5.71% probability that, for a sample of 40 college games to be played next week, the mean number of holding penalties will be 2 penalties per game or less

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