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Anna007 [38]
3 years ago
15

The equation h = -16t^2 + 32t + 9 gives the height of a ball, h, in feet above the ground, at t seconds after the ball is thrown

upward. How many seconds after the ball is thrown will it reach its maximum height? What is its maximum height?
Mathematics
1 answer:
belka [17]3 years ago
6 0
<span>It would take 1 second to reach its maximum height, which would be 25 feet.

h=<span><span><span>−<span>16<span>(<span>1^2</span>)</span></span></span>+<span><span>(32)</span><span>(1)</span></span></span>+<span>9 If you substituted t as 1, you would find that after simplification, h would be 25.

You would find out that as you increased t, h would get smaller.
</span></span></span>
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P(X&lt; ) 1-P(X&gt; ) A softball pitcher has a 0.626 probability of throwing a strike for each curve ball pitch. If the softball
Mashutka [201]

Answer:

19.49% probability that no more than 16 of them are strikes

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

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.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

n = 30, p = 0.626

So

\mu = E(X) = np = 30*0.626 = 18.78

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{30*0.626*0.374} = 2.65

What is the probability that no more than 16 of them are strikes?

Using continuity correction, this is P(X \leq 16 + 0.5) = P(X \leq 16.5), which is the pvalue of Z when X = 16.5. So

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

Z = \frac{16.5 - 18.78}{2.65}

Z = -0.86

Z = -0.86 has a pvalue of 0.1949

19.49% probability that no more than 16 of them are strikes

7 0
3 years ago
If x = -1, then which of the following equations makes a true statement
uranmaximum [27]
Only the third one makes x=-1 true
7 0
3 years ago
Alex wants to cover his wall
alexandr1967 [171]

Answer: A = π r2

r=8 and 8 squared is 64 and 64×3.14=200.96 or rounded to the nearest whole number it would be 201

Step-by-step explanation: brainliest please?

5 0
2 years ago
A) -10 &lt; y &lt; 10 <br><br> B) -2 &lt; y &lt; 7 <br><br> C) { -2, 1, 4, 7 } <br><br> D) { -2, 7 }
nekit [7.7K]
The answer to this should be b

7 0
3 years ago
-18.3 = b + -8.3<br> b =
Sauron [17]

Answer:

Here,

-18.3=b+ -8.3

-18.3+8.3=b

-10=b

the value of b is -10.

3 0
3 years ago
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